05_strategy_evaluation/01_backtest_with_trades.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# zipline MeanReversion Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the chapter 04, we introduced `Zipline` to simulate the computation of alpha factors from trailing cross-sectional market, fundamental, and alternative data.\n",
    "\n",
    "Now we will exploit the alpha factors to derive and act on buy and sell signals using the custom MeanReversion factor developed in the last chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:43.166604Z",
     "start_time": "2021-04-15T19:45:43.164646Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.405761Z",
     "start_time": "2021-04-15T19:45:43.169291Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pytz import UTC\n",
    "\n",
    "from logbook import (NestedSetup, NullHandler, Logger, StreamHandler, StderrHandler, \n",
    "                     INFO, WARNING, DEBUG, ERROR)\n",
    "\n",
    "from zipline import run_algorithm\n",
    "from zipline.api import (attach_pipeline, \n",
    "                         date_rules, \n",
    "                         time_rules,\n",
    "                         get_datetime,\n",
    "                         order_target_percent,\n",
    "                         pipeline_output, \n",
    "                         record, \n",
    "                         schedule_function, \n",
    "                         get_open_orders, \n",
    "                         calendars,\n",
    "                         set_commission, \n",
    "                         set_slippage)\n",
    "from zipline.finance import commission, slippage\n",
    "from zipline.pipeline import Pipeline, CustomFactor\n",
    "from zipline.pipeline.factors import Returns, AverageDollarVolume\n",
    "\n",
    "from pyfolio.utils import extract_rets_pos_txn_from_zipline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.408609Z",
     "start_time": "2021-04-15T19:45:44.406742Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logging Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.443817Z",
     "start_time": "2021-04-15T19:45:44.409938Z"
    }
   },
   "outputs": [],
   "source": [
    "# setup stdout logging\n",
    "format_string = '[{record.time: %H:%M:%S.%f}]: {record.level_name}: {record.message}'\n",
    "zipline_logging = NestedSetup([NullHandler(level=DEBUG),\n",
    "                               StreamHandler(sys.stdout, format_string=format_string, level=INFO),\n",
    "                               StreamHandler(sys.stderr, level=ERROR)])\n",
    "zipline_logging.push_application()\n",
    "log = Logger('Algorithm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algo Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.459887Z",
     "start_time": "2021-04-15T19:45:44.449863Z"
    }
   },
   "outputs": [],
   "source": [
    "# Settings\n",
    "MONTH = 21\n",
    "YEAR = 12 * MONTH\n",
    "N_LONGS = 50\n",
    "N_SHORTS = 50\n",
    "VOL_SCREEN = 500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.469828Z",
     "start_time": "2021-04-15T19:45:44.464068Z"
    }
   },
   "outputs": [],
   "source": [
    "start = pd.Timestamp('2013-01-01', tz=UTC)\n",
    "end = pd.Timestamp('2017-01-01', tz=UTC)\n",
    "capital_base = 1e7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion Factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.478710Z",
     "start_time": "2021-04-15T19:45:44.472136Z"
    }
   },
   "outputs": [],
   "source": [
    "class MeanReversion(CustomFactor):\n",
    "    \"\"\"Compute ratio of latest monthly return to 12m average,\n",
    "       normalized by std dev of monthly returns\"\"\"\n",
    "    inputs = [Returns(window_length=MONTH)]\n",
    "    window_length = YEAR\n",
    "\n",
    "    def compute(self, today, assets, out, monthly_returns):\n",
    "        df = pd.DataFrame(monthly_returns)\n",
    "        out[:] = df.iloc[-1].sub(df.mean()).div(df.std())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Pipeline created by the `compute_factors()` method returns a table with a long and a short column for the 25 stocks with the largest negative and positive deviations of their last monthly return from its annual average, normalized by the standard deviation. It also limited the universe to the 500 stocks with the highest average trading volume over the last 30 trading days. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.486790Z",
     "start_time": "2021-04-15T19:45:44.480301Z"
    }
   },
   "outputs": [],
   "source": [
    "def compute_factors():\n",
    "    \"\"\"Create factor pipeline incl. mean reversion,\n",
    "        filtered by 30d Dollar Volume; capture factor ranks\"\"\"\n",
    "    mean_reversion = MeanReversion()\n",
    "    dollar_volume = AverageDollarVolume(window_length=30)\n",
    "    return Pipeline(columns={'longs'  : mean_reversion.bottom(N_LONGS),\n",
    "                             'shorts' : mean_reversion.top(N_SHORTS),\n",
    "                             'ranking': mean_reversion.rank(ascending=False)},\n",
    "                    screen=dollar_volume.top(VOL_SCREEN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before_trading_start() ensures the daily execution of the pipeline and the recording of the results, including the current prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.494999Z",
     "start_time": "2021-04-15T19:45:44.489010Z"
    }
   },
   "outputs": [],
   "source": [
    "def before_trading_start(context, data):\n",
    "    \"\"\"Run factor pipeline\"\"\"\n",
    "    context.factor_data = pipeline_output('factor_pipeline')\n",
    "    record(factor_data=context.factor_data.ranking)\n",
    "    assets = context.factor_data.index\n",
    "    record(prices=data.current(assets, 'price'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Rebalancing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The new rebalance() method submits trade orders to the exec_trades() method for the assets flagged for long and short positions by the pipeline with equal positive and negative weights. It also divests any current holdings that are no longer included in the factor signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.502894Z",
     "start_time": "2021-04-15T19:45:44.496575Z"
    }
   },
   "outputs": [],
   "source": [
    "def rebalance(context, data):\n",
    "    \"\"\"Compute long, short and obsolete holdings; place trade orders\"\"\"\n",
    "    factor_data = context.factor_data\n",
    "    assets = factor_data.index\n",
    "    \n",
    "    longs = assets[factor_data.longs]\n",
    "    shorts = assets[factor_data.shorts]\n",
    "    divest = context.portfolio.positions.keys() - longs.union(shorts)\n",
    "    log.info('{} | Longs: {:2.0f} | Shorts: {:2.0f} | {:,.2f}'.format(get_datetime().date(),\n",
    "                                                                     len(longs), \n",
    "                                                                     len(shorts),\n",
    "                                                                     context.portfolio.portfolio_value))\n",
    "\n",
    "    exec_trades(data, assets=divest, target_percent=0)\n",
    "    exec_trades(data, assets=longs, target_percent=1 / N_LONGS if N_LONGS else 0)\n",
    "    exec_trades(data, assets=shorts, target_percent=-1 / N_SHORTS if N_SHORTS else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.513490Z",
     "start_time": "2021-04-15T19:45:44.503906Z"
    }
   },
   "outputs": [],
   "source": [
    "def exec_trades(data, assets, target_percent):\n",
    "    \"\"\"Place orders for assets using target portfolio percentage\"\"\"\n",
    "    for asset in assets:\n",
    "        if data.can_trade(asset) and not get_open_orders(asset):\n",
    "            order_target_percent(asset, target_percent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `rebalance()` method runs according to `date_rules` and `time_rules` set by the `schedule_function()` utility at the beginning of the week, right after market_open as stipulated by the built-in US_EQUITIES calendar (see docs for details on rules). \n",
    "\n",
    "You can also specify a trade commission both in relative terms and as a minimum amount. There is also an option to define slippage, which is the cost of an adverse change in price between trade decision and execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:45:44.521659Z",
     "start_time": "2021-04-15T19:45:44.514324Z"
    }
   },
   "outputs": [],
   "source": [
    "def initialize(context):\n",
    "    \"\"\"Setup: register pipeline, schedule rebalancing,\n",
    "        and set trading params\"\"\"\n",
    "    attach_pipeline(compute_factors(), 'factor_pipeline')\n",
    "    schedule_function(rebalance,\n",
    "                      date_rules.week_start(),\n",
    "                      time_rules.market_open(),\n",
    "                      calendar=calendars.US_EQUITIES)\n",
    "\n",
    "    set_commission(us_equities=commission.PerShare(cost=0.00075, \n",
    "                                                   min_trade_cost=.01))\n",
    "    set_slippage(us_equities=slippage.VolumeShareSlippage(volume_limit=0.0025, \n",
    "                                                          price_impact=0.01))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The algorithm executes upon calling the run_algorithm() function and returns the backtest performance DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:09.694529Z",
     "start_time": "2021-04-15T19:45:44.522485Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 19:45:47.847522]: INFO: 2013-01-07 | Longs: 10 | Shorts:  2 | 10,000,000.00\n",
      "[ 19:45:52.095417]: INFO: 2013-01-14 | Longs: 13 | Shorts:  3 | 10,027,422.36\n",
      "[ 19:45:52.700469]: INFO: 2013-01-22 | Longs:  8 | Shorts:  5 | 10,097,663.57\n",
      "[ 19:45:53.190897]: INFO: 2013-01-28 | Longs:  5 | Shorts: 14 | 10,106,150.06\n",
      "[ 19:45:53.810739]: INFO: 2013-02-04 | Longs: 12 | Shorts: 11 | 10,135,417.26\n",
      "[ 19:45:54.448141]: INFO: 2013-02-11 | Longs: 11 | Shorts: 13 | 10,182,644.42\n",
      "[ 19:45:55.093475]: INFO: 2013-02-19 | Longs: 21 | Shorts: 11 | 10,127,755.45\n",
      "[ 19:45:55.646754]: INFO: 2013-02-25 | Longs: 16 | Shorts:  8 | 10,180,357.23\n",
      "[ 19:45:56.316751]: INFO: 2013-03-04 | Longs: 10 | Shorts: 10 | 10,200,300.19\n",
      "[ 19:45:56.942645]: INFO: 2013-03-11 | Longs: 12 | Shorts:  7 | 10,240,453.13\n",
      "[ 19:45:57.560857]: INFO: 2013-03-18 | Longs:  7 | Shorts:  7 | 10,150,394.01\n",
      "[ 19:45:58.174192]: INFO: 2013-03-25 | Longs:  8 | Shorts:  7 | 10,149,029.25\n",
      "[ 19:45:58.673395]: INFO: 2013-04-01 | Longs:  4 | Shorts:  6 | 10,178,638.39\n",
      "[ 19:45:59.255032]: INFO: 2013-04-08 | Longs:  6 | Shorts: 13 | 10,188,518.05\n",
      "[ 19:45:59.870276]: INFO: 2013-04-15 | Longs:  5 | Shorts: 14 | 10,185,696.44\n",
      "[ 19:46:00.499841]: INFO: 2013-04-22 | Longs:  5 | Shorts: 24 | 10,154,587.17\n",
      "[ 19:46:01.161558]: INFO: 2013-04-29 | Longs:  5 | Shorts: 10 | 10,189,194.78\n",
      "[ 19:46:01.801803]: INFO: 2013-05-06 | Longs:  2 | Shorts: 10 | 10,166,211.32\n",
      "[ 19:46:02.402998]: INFO: 2013-05-13 | Longs:  4 | Shorts:  8 | 9,981,220.24\n",
      "[ 19:46:02.981176]: INFO: 2013-05-20 | Longs:  8 | Shorts:  9 | 9,943,518.58\n",
      "[ 19:46:03.574252]: INFO: 2013-05-28 | Longs: 13 | Shorts:  5 | 9,905,180.12\n",
      "[ 19:46:04.081390]: INFO: 2013-06-03 | Longs: 19 | Shorts:  6 | 9,962,705.11\n",
      "[ 19:46:04.716038]: INFO: 2013-06-10 | Longs: 10 | Shorts:  3 | 9,953,403.78\n",
      "[ 19:46:05.341995]: INFO: 2013-06-17 | Longs:  9 | Shorts:  6 | 9,978,043.58\n",
      "[ 19:46:05.935565]: INFO: 2013-06-24 | Longs:  9 | Shorts:  2 | 9,875,082.86\n",
      "[ 19:46:06.521659]: INFO: 2013-07-01 | Longs: 15 | Shorts:  3 | 9,932,122.01\n",
      "[ 19:46:07.025303]: INFO: 2013-07-08 | Longs: 13 | Shorts:  3 | 9,976,143.93\n",
      "[ 19:46:09.239819]: INFO: 2013-07-15 | Longs: 11 | Shorts:  4 | 10,094,240.18\n",
      "[ 19:46:09.846010]: INFO: 2013-07-22 | Longs:  6 | Shorts:  2 | 10,056,638.95\n",
      "[ 19:46:10.440213]: INFO: 2013-07-29 | Longs: 12 | Shorts:  3 | 10,051,076.70\n",
      "[ 19:46:11.025538]: INFO: 2013-08-05 | Longs:  8 | Shorts: 12 | 10,138,418.95\n",
      "[ 19:46:11.643550]: INFO: 2013-08-12 | Longs:  7 | Shorts: 10 | 10,146,586.21\n",
      "[ 19:46:12.256360]: INFO: 2013-08-19 | Longs:  7 | Shorts:  9 | 10,181,590.85\n",
      "[ 19:46:12.861775]: INFO: 2013-08-26 | Longs:  7 | Shorts:  2 | 10,178,592.71\n",
      "[ 19:46:13.450842]: INFO: 2013-09-03 | Longs:  5 | Shorts:  2 | 10,226,884.83\n",
      "[ 19:46:13.908184]: INFO: 2013-09-09 | Longs:  6 | Shorts:  4 | 10,210,627.07\n",
      "[ 19:46:14.476657]: INFO: 2013-09-16 | Longs:  6 | Shorts:  5 | 10,266,501.96\n",
      "[ 19:46:15.061177]: INFO: 2013-09-23 | Longs:  6 | Shorts:  3 | 10,258,815.75\n",
      "[ 19:46:15.636866]: INFO: 2013-09-30 | Longs: 10 | Shorts:  8 | 10,233,855.17\n",
      "[ 19:46:16.234862]: INFO: 2013-10-07 | Longs: 13 | Shorts:  7 | 10,227,149.62\n",
      "[ 19:46:16.852245]: INFO: 2013-10-14 | Longs: 14 | Shorts:  3 | 10,278,149.27\n",
      "[ 19:46:17.465788]: INFO: 2013-10-21 | Longs: 15 | Shorts:  8 | 10,187,013.14\n",
      "[ 19:46:18.096059]: INFO: 2013-10-28 | Longs: 11 | Shorts:  6 | 10,323,170.17\n",
      "[ 19:46:18.717588]: INFO: 2013-11-04 | Longs:  6 | Shorts: 10 | 10,214,759.93\n",
      "[ 19:46:19.327792]: INFO: 2013-11-11 | Longs:  2 | Shorts:  5 | 10,257,347.04\n",
      "[ 19:46:19.915615]: INFO: 2013-11-18 | Longs:  4 | Shorts:  9 | 10,245,333.87\n",
      "[ 19:46:20.502456]: INFO: 2013-11-25 | Longs:  4 | Shorts:  8 | 10,279,469.50\n",
      "[ 19:46:20.988722]: INFO: 2013-12-02 | Longs:  7 | Shorts:  2 | 10,302,532.04\n",
      "[ 19:46:21.572209]: INFO: 2013-12-09 | Longs: 10 | Shorts:  3 | 10,320,355.73\n",
      "[ 19:46:22.162478]: INFO: 2013-12-16 | Longs: 17 | Shorts:  2 | 10,353,234.81\n",
      "[ 19:46:22.828759]: INFO: 2013-12-23 | Longs: 11 | Shorts:  4 | 10,269,888.43\n",
      "[ 19:46:23.341442]: INFO: 2013-12-30 | Longs: 10 | Shorts:  6 | 10,293,416.34\n",
      "[ 19:46:23.831108]: INFO: 2014-01-06 | Longs: 12 | Shorts:  5 | 10,300,370.23\n",
      "[ 19:46:24.431977]: INFO: 2014-01-13 | Longs:  8 | Shorts:  3 | 10,321,419.65\n",
      "[ 19:46:26.736086]: INFO: 2014-01-21 | Longs: 14 | Shorts:  4 | 10,301,321.23\n",
      "[ 19:46:27.234386]: INFO: 2014-01-27 | Longs: 16 | Shorts:  4 | 10,272,301.28\n",
      "[ 19:46:27.854221]: INFO: 2014-02-03 | Longs: 16 | Shorts:  7 | 10,190,046.47\n",
      "[ 19:46:28.477219]: INFO: 2014-02-10 | Longs: 10 | Shorts:  8 | 10,173,544.07\n",
      "[ 19:46:29.093780]: INFO: 2014-02-18 | Longs:  8 | Shorts: 11 | 10,146,175.51\n",
      "[ 19:46:29.588348]: INFO: 2014-02-24 | Longs:  8 | Shorts: 11 | 10,135,284.41\n",
      "[ 19:46:30.193018]: INFO: 2014-03-03 | Longs:  5 | Shorts: 10 | 10,206,465.49\n",
      "[ 19:46:30.794267]: INFO: 2014-03-10 | Longs:  8 | Shorts:  5 | 10,193,416.12\n",
      "[ 19:46:31.376171]: INFO: 2014-03-17 | Longs:  6 | Shorts:  4 | 10,150,092.53\n",
      "[ 19:46:31.945393]: INFO: 2014-03-24 | Longs:  7 | Shorts:  3 | 10,157,127.09\n",
      "[ 19:46:32.519026]: INFO: 2014-03-31 | Longs: 10 | Shorts:  3 | 10,127,717.05\n",
      "[ 19:46:33.112206]: INFO: 2014-04-07 | Longs: 10 | Shorts: 10 | 9,940,554.60\n",
      "[ 19:46:33.719175]: INFO: 2014-04-14 | Longs: 10 | Shorts: 12 | 9,922,172.04\n",
      "[ 19:46:34.231646]: INFO: 2014-04-21 | Longs:  9 | Shorts: 16 | 9,977,695.73\n",
      "[ 19:46:34.878499]: INFO: 2014-04-28 | Longs:  8 | Shorts: 11 | 9,925,818.81\n",
      "[ 19:46:35.505814]: INFO: 2014-05-05 | Longs:  6 | Shorts:  8 | 9,994,098.05\n",
      "[ 19:46:36.106871]: INFO: 2014-05-12 | Longs:  3 | Shorts:  9 | 9,959,988.27\n",
      "[ 19:46:36.694084]: INFO: 2014-05-19 | Longs:  2 | Shorts:  6 | 9,952,316.59\n",
      "[ 19:46:37.255650]: INFO: 2014-05-27 | Longs:  5 | Shorts:  5 | 9,975,477.08\n",
      "[ 19:46:37.725009]: INFO: 2014-06-02 | Longs:  6 | Shorts:  3 | 9,987,026.35\n",
      "[ 19:46:38.297596]: INFO: 2014-06-09 | Longs:  8 | Shorts:  5 | 10,024,385.61\n",
      "[ 19:46:38.889416]: INFO: 2014-06-16 | Longs: 13 | Shorts: 13 | 9,983,402.35\n",
      "[ 19:46:39.531742]: INFO: 2014-06-23 | Longs:  8 | Shorts: 15 | 9,996,939.06\n",
      "[ 19:46:40.176475]: INFO: 2014-06-30 | Longs: 12 | Shorts: 15 | 10,037,014.26\n",
      "[ 19:46:40.712931]: INFO: 2014-07-07 | Longs: 14 | Shorts: 12 | 10,082,385.12\n",
      "[ 19:46:41.360016]: INFO: 2014-07-14 | Longs:  5 | Shorts: 14 | 10,089,176.51\n",
      "[ 19:46:43.605913]: INFO: 2014-07-21 | Longs: 13 | Shorts: 11 | 10,128,809.09\n",
      "[ 19:46:44.252207]: INFO: 2014-07-28 | Longs: 11 | Shorts: 11 | 10,119,893.60\n",
      "[ 19:46:44.887652]: INFO: 2014-08-04 | Longs: 11 | Shorts: 19 | 10,110,604.81\n",
      "[ 19:46:45.559208]: INFO: 2014-08-11 | Longs: 14 | Shorts: 11 | 10,259,687.80\n",
      "[ 19:46:46.223072]: INFO: 2014-08-18 | Longs: 11 | Shorts: 14 | 10,204,032.36\n",
      "[ 19:46:46.865650]: INFO: 2014-08-25 | Longs: 12 | Shorts: 14 | 10,211,914.68\n",
      "[ 19:46:47.532028]: INFO: 2014-09-02 | Longs:  7 | Shorts:  9 | 10,176,282.96\n",
      "[ 19:46:48.087475]: INFO: 2014-09-08 | Longs:  2 | Shorts: 13 | 10,227,375.20\n",
      "[ 19:46:48.690214]: INFO: 2014-09-15 | Longs:  5 | Shorts:  4 | 10,232,017.60\n",
      "[ 19:46:49.278901]: INFO: 2014-09-22 | Longs:  6 | Shorts:  8 | 10,188,352.29\n",
      "[ 19:46:49.864395]: INFO: 2014-09-29 | Longs:  4 | Shorts: 13 | 10,153,790.76\n",
      "[ 19:46:50.465842]: INFO: 2014-10-06 | Longs: 12 | Shorts:  9 | 10,137,941.09\n",
      "[ 19:46:51.088348]: INFO: 2014-10-13 | Longs: 12 | Shorts: 17 | 10,008,763.46\n",
      "[ 19:46:51.789845]: INFO: 2014-10-20 | Longs: 21 | Shorts:  6 | 10,132,979.74\n",
      "[ 19:46:52.464740]: INFO: 2014-10-27 | Longs: 13 | Shorts:  7 | 10,130,508.74\n",
      "[ 19:46:53.109743]: INFO: 2014-11-03 | Longs:  6 | Shorts:  0 | 10,202,585.17\n",
      "[ 19:46:53.696345]: INFO: 2014-11-10 | Longs:  7 | Shorts:  6 | 10,112,658.72\n",
      "[ 19:46:54.281286]: INFO: 2014-11-17 | Longs:  6 | Shorts: 10 | 10,149,797.97\n",
      "[ 19:46:54.880329]: INFO: 2014-11-24 | Longs:  6 | Shorts:  7 | 10,159,664.13\n",
      "[ 19:46:55.363560]: INFO: 2014-12-01 | Longs: 12 | Shorts: 13 | 10,112,949.01\n",
      "[ 19:46:56.008206]: INFO: 2014-12-08 | Longs: 11 | Shorts:  4 | 9,883,877.18\n",
      "[ 19:46:56.621757]: INFO: 2014-12-15 | Longs: 13 | Shorts:  3 | 9,748,742.24\n",
      "[ 19:46:57.211873]: INFO: 2014-12-22 | Longs:  7 | Shorts:  4 | 10,162,433.56\n",
      "[ 19:46:57.700293]: INFO: 2014-12-29 | Longs: 10 | Shorts:  8 | 10,153,178.89\n",
      "[ 19:46:58.195367]: INFO: 2015-01-05 | Longs:  6 | Shorts:  3 | 10,058,855.77\n",
      "[ 19:46:58.779960]: INFO: 2015-01-12 | Longs:  7 | Shorts:  6 | 10,013,742.96\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 19:47:00.983066]: INFO: 2015-01-20 | Longs: 12 | Shorts:  7 | 9,911,930.16\n",
      "[ 19:47:01.477727]: INFO: 2015-01-26 | Longs: 11 | Shorts:  8 | 9,933,179.35\n",
      "[ 19:47:02.097079]: INFO: 2015-02-02 | Longs: 18 | Shorts:  7 | 9,874,894.91\n",
      "[ 19:47:02.753928]: INFO: 2015-02-09 | Longs: 15 | Shorts:  6 | 10,026,955.51\n",
      "[ 19:47:03.391743]: INFO: 2015-02-17 | Longs: 12 | Shorts: 11 | 10,080,570.15\n",
      "[ 19:47:03.912410]: INFO: 2015-02-23 | Longs: 13 | Shorts:  7 | 10,087,564.34\n",
      "[ 19:47:04.539404]: INFO: 2015-03-02 | Longs: 16 | Shorts:  7 | 10,042,612.79\n",
      "[ 19:47:05.185830]: INFO: 2015-03-09 | Longs: 12 | Shorts:  5 | 9,963,112.34\n",
      "[ 19:47:05.953729]: INFO: 2015-03-16 | Longs: 15 | Shorts:  2 | 10,023,732.49\n",
      "[ 19:47:06.644113]: INFO: 2015-03-23 | Longs: 10 | Shorts:  2 | 10,078,627.34\n",
      "[ 19:47:07.381910]: INFO: 2015-03-30 | Longs: 13 | Shorts:  4 | 10,072,282.97\n",
      "[ 19:47:07.875927]: INFO: 2015-04-06 | Longs: 12 | Shorts:  3 | 10,123,357.71\n",
      "[ 19:47:08.473323]: INFO: 2015-04-13 | Longs:  5 | Shorts:  8 | 10,165,443.63\n",
      "[ 19:47:09.071872]: INFO: 2015-04-20 | Longs: 14 | Shorts: 11 | 10,161,371.72\n",
      "[ 19:47:09.718897]: INFO: 2015-04-27 | Longs: 12 | Shorts:  9 | 10,114,674.77\n",
      "[ 19:47:10.361190]: INFO: 2015-05-04 | Longs:  8 | Shorts: 13 | 10,111,362.19\n",
      "[ 19:47:11.004516]: INFO: 2015-05-11 | Longs:  7 | Shorts:  8 | 10,117,885.18\n",
      "[ 19:47:11.623698]: INFO: 2015-05-18 | Longs:  5 | Shorts:  7 | 10,118,338.65\n",
      "[ 19:47:12.214493]: INFO: 2015-05-26 | Longs:  3 | Shorts:  5 | 10,125,037.38\n",
      "[ 19:47:12.687940]: INFO: 2015-06-01 | Longs:  5 | Shorts:  8 | 10,140,937.50\n",
      "[ 19:47:13.273093]: INFO: 2015-06-08 | Longs: 10 | Shorts:  6 | 10,160,546.75\n",
      "[ 19:47:13.875858]: INFO: 2015-06-15 | Longs: 14 | Shorts:  6 | 10,135,990.35\n",
      "[ 19:47:14.507273]: INFO: 2015-06-22 | Longs: 10 | Shorts:  4 | 10,244,177.64\n",
      "[ 19:47:15.125479]: INFO: 2015-06-29 | Longs: 18 | Shorts:  5 | 10,137,986.21\n",
      "[ 19:47:15.639425]: INFO: 2015-07-06 | Longs: 12 | Shorts: 10 | 10,170,113.59\n",
      "[ 19:47:16.274104]: INFO: 2015-07-13 | Longs:  7 | Shorts:  7 | 10,244,091.21\n",
      "[ 19:47:16.890872]: INFO: 2015-07-20 | Longs:  5 | Shorts: 11 | 10,240,223.17\n",
      "[ 19:47:19.076221]: INFO: 2015-07-27 | Longs:  7 | Shorts: 13 | 10,311,588.77\n",
      "[ 19:47:19.685814]: INFO: 2015-08-03 | Longs:  5 | Shorts: 12 | 10,277,581.93\n",
      "[ 19:47:20.300030]: INFO: 2015-08-10 | Longs:  3 | Shorts: 11 | 10,308,010.70\n",
      "[ 19:47:20.899285]: INFO: 2015-08-17 | Longs:  5 | Shorts:  8 | 10,274,866.69\n",
      "[ 19:47:21.515497]: INFO: 2015-08-24 | Longs: 17 | Shorts:  7 | 10,262,054.06\n",
      "[ 19:47:22.140685]: INFO: 2015-08-31 | Longs: 14 | Shorts:  5 | 10,388,393.11\n",
      "[ 19:47:22.759612]: INFO: 2015-09-08 | Longs: 21 | Shorts:  5 | 10,453,422.88\n",
      "[ 19:47:23.291611]: INFO: 2015-09-14 | Longs: 11 | Shorts:  8 | 10,407,866.97\n",
      "[ 19:47:23.924105]: INFO: 2015-09-21 | Longs: 12 | Shorts:  9 | 10,461,020.10\n",
      "[ 19:47:24.550563]: INFO: 2015-09-28 | Longs: 15 | Shorts:  7 | 10,413,522.87\n",
      "[ 19:47:25.186792]: INFO: 2015-10-05 | Longs:  2 | Shorts:  7 | 10,684,535.25\n",
      "[ 19:47:25.788689]: INFO: 2015-10-12 | Longs: 10 | Shorts:  7 | 10,677,559.63\n",
      "[ 19:47:26.398941]: INFO: 2015-10-19 | Longs:  6 | Shorts:  8 | 10,720,533.14\n",
      "[ 19:47:26.999715]: INFO: 2015-10-26 | Longs: 11 | Shorts: 12 | 10,585,301.22\n",
      "[ 19:47:27.629153]: INFO: 2015-11-02 | Longs: 14 | Shorts:  6 | 10,594,718.88\n",
      "[ 19:47:28.262618]: INFO: 2015-11-09 | Longs: 10 | Shorts:  5 | 10,402,671.77\n",
      "[ 19:47:28.875914]: INFO: 2015-11-16 | Longs: 13 | Shorts:  5 | 10,375,441.10\n",
      "[ 19:47:29.040622]: INFO: after split: asset: Equity(406 [BOFI]), amount: 1616, cost_basis: 23.48, last_sale_price: 83.29\n",
      "[ 19:47:29.041061]: INFO: returning cash: 0.0\n",
      "[ 19:47:29.496124]: INFO: 2015-11-23 | Longs:  9 | Shorts:  7 | 10,449,719.61\n",
      "[ 19:47:30.007682]: INFO: 2015-11-30 | Longs: 11 | Shorts:  6 | 10,496,308.50\n",
      "[ 19:47:30.625996]: INFO: 2015-12-07 | Longs: 12 | Shorts:  8 | 10,513,409.39\n",
      "[ 19:47:31.246652]: INFO: 2015-12-14 | Longs:  9 | Shorts: 14 | 10,400,063.33\n",
      "[ 19:47:31.895426]: INFO: 2015-12-21 | Longs: 10 | Shorts: 12 | 10,336,091.55\n",
      "[ 19:47:32.429951]: INFO: 2015-12-28 | Longs:  9 | Shorts:  8 | 10,373,369.95\n",
      "[ 19:47:32.955684]: INFO: 2016-01-04 | Longs:  5 | Shorts: 11 | 10,377,997.16\n",
      "[ 19:47:33.561514]: INFO: 2016-01-11 | Longs:  8 | Shorts:  7 | 10,413,318.21\n",
      "[ 19:47:34.178342]: INFO: 2016-01-19 | Longs:  8 | Shorts:  6 | 10,454,666.31\n",
      "[ 19:47:36.204941]: INFO: 2016-01-25 | Longs:  9 | Shorts:  9 | 10,477,454.93\n",
      "[ 19:47:36.814962]: INFO: 2016-02-01 | Longs: 14 | Shorts: 14 | 10,420,206.34\n",
      "[ 19:47:37.475246]: INFO: 2016-02-08 | Longs: 18 | Shorts: 16 | 10,182,460.84\n",
      "[ 19:47:38.176049]: INFO: 2016-02-16 | Longs: 12 | Shorts: 10 | 10,452,919.06\n",
      "[ 19:47:38.732747]: INFO: 2016-02-22 | Longs:  6 | Shorts:  7 | 10,585,928.85\n",
      "[ 19:47:39.358521]: INFO: 2016-02-29 | Longs:  4 | Shorts:  9 | 10,622,313.10\n",
      "[ 19:47:39.966348]: INFO: 2016-03-07 | Longs:  9 | Shorts:  8 | 10,558,809.60\n",
      "[ 19:47:40.598327]: INFO: 2016-03-14 | Longs:  4 | Shorts:  4 | 10,554,090.86\n",
      "[ 19:47:41.203249]: INFO: 2016-03-21 | Longs:  5 | Shorts: 10 | 10,327,145.78\n",
      "[ 19:47:41.708528]: INFO: 2016-03-28 | Longs:  5 | Shorts:  4 | 10,457,227.91\n",
      "[ 19:47:42.303564]: INFO: 2016-04-04 | Longs:  3 | Shorts:  2 | 10,406,360.98\n",
      "[ 19:47:42.892175]: INFO: 2016-04-11 | Longs:  7 | Shorts:  9 | 10,409,222.16\n",
      "[ 19:47:43.538288]: INFO: 2016-04-18 | Longs: 15 | Shorts:  6 | 10,400,049.03\n",
      "[ 19:47:44.236621]: INFO: 2016-04-25 | Longs: 19 | Shorts:  2 | 10,404,515.45\n",
      "[ 19:47:44.933809]: INFO: 2016-05-02 | Longs: 13 | Shorts:  9 | 10,431,469.55\n",
      "[ 19:47:45.595158]: INFO: 2016-05-09 | Longs: 10 | Shorts:  2 | 10,524,765.67\n",
      "[ 19:47:46.229593]: INFO: 2016-05-16 | Longs: 14 | Shorts:  6 | 10,468,602.90\n",
      "[ 19:47:46.868840]: INFO: 2016-05-23 | Longs: 11 | Shorts:  7 | 10,485,867.14\n",
      "[ 19:47:47.519156]: INFO: 2016-05-31 | Longs:  7 | Shorts:  7 | 10,535,395.41\n",
      "[ 19:47:48.047921]: INFO: 2016-06-06 | Longs:  9 | Shorts:  9 | 10,549,440.76\n",
      "[ 19:47:48.653117]: INFO: 2016-06-13 | Longs: 13 | Shorts:  6 | 10,605,810.71\n",
      "[ 19:47:49.275752]: INFO: 2016-06-20 | Longs:  8 | Shorts:  6 | 10,589,211.73\n",
      "[ 19:47:49.892499]: INFO: 2016-06-27 | Longs: 17 | Shorts:  4 | 10,483,875.66\n",
      "[ 19:47:50.512126]: INFO: 2016-07-05 | Longs:  6 | Shorts: 12 | 10,575,846.46\n",
      "[ 19:47:51.019847]: INFO: 2016-07-11 | Longs:  7 | Shorts: 11 | 10,662,656.13\n",
      "[ 19:47:51.637688]: INFO: 2016-07-18 | Longs:  3 | Shorts:  5 | 10,683,919.69\n",
      "[ 19:47:55.667261]: INFO: 2016-07-25 | Longs:  7 | Shorts: 13 | 10,707,303.42\n",
      "[ 19:47:56.270324]: INFO: 2016-08-01 | Longs: 14 | Shorts:  8 | 10,718,980.24\n",
      "[ 19:47:56.909125]: INFO: 2016-08-08 | Longs: 12 | Shorts:  7 | 10,660,895.86\n",
      "[ 19:47:57.548971]: INFO: 2016-08-15 | Longs:  7 | Shorts:  8 | 10,665,800.53\n",
      "[ 19:47:58.199619]: INFO: 2016-08-22 | Longs:  8 | Shorts:  6 | 10,650,245.31\n",
      "[ 19:47:58.815117]: INFO: 2016-08-29 | Longs: 11 | Shorts:  3 | 10,649,100.18\n",
      "[ 19:47:59.414821]: INFO: 2016-09-06 | Longs: 14 | Shorts:  5 | 10,654,268.58\n",
      "[ 19:47:59.924402]: INFO: 2016-09-12 | Longs: 29 | Shorts:  3 | 10,636,322.37\n",
      "[ 19:48:00.616401]: INFO: 2016-09-19 | Longs: 19 | Shorts:  5 | 10,675,288.81\n",
      "[ 19:48:01.315263]: INFO: 2016-09-26 | Longs: 14 | Shorts:  5 | 10,680,478.84\n",
      "[ 19:48:01.967420]: INFO: 2016-10-03 | Longs: 10 | Shorts:  5 | 10,723,923.98\n",
      "[ 19:48:02.577480]: INFO: 2016-10-10 | Longs:  5 | Shorts:  5 | 10,708,120.44\n",
      "[ 19:48:03.178193]: INFO: 2016-10-17 | Longs:  6 | Shorts:  6 | 10,748,231.24\n",
      "[ 19:48:03.759245]: INFO: 2016-10-24 | Longs:  5 | Shorts: 11 | 10,743,221.29\n",
      "[ 19:48:04.365393]: INFO: 2016-10-31 | Longs:  7 | Shorts: 15 | 10,761,910.49\n",
      "[ 19:48:04.987985]: INFO: 2016-11-07 | Longs: 11 | Shorts: 11 | 10,739,304.47\n",
      "[ 19:48:05.620129]: INFO: 2016-11-14 | Longs: 18 | Shorts:  4 | 10,691,323.41\n",
      "[ 19:48:06.263074]: INFO: 2016-11-21 | Longs: 18 | Shorts:  1 | 10,734,499.53\n",
      "[ 19:48:06.763776]: INFO: 2016-11-28 | Longs: 20 | Shorts:  0 | 10,724,702.90\n",
      "[ 19:48:07.384120]: INFO: 2016-12-05 | Longs: 25 | Shorts:  3 | 10,679,618.01\n",
      "[ 19:48:08.027829]: INFO: 2016-12-12 | Longs: 21 | Shorts:  1 | 10,835,582.73\n",
      "[ 19:48:08.682182]: INFO: 2016-12-19 | Longs: 13 | Shorts:  2 | 10,871,411.67\n",
      "[ 19:48:09.296106]: INFO: 2016-12-27 | Longs: 12 | Shorts:  1 | 10,815,943.67\n",
      "[ 19:48:09.677636]: INFO: Simulated 1008 trading days\n",
      "first open: 2013-01-02 14:31:00+00:00\n",
      "last close: 2016-12-30 21:00:00+00:00\n"
     ]
    }
   ],
   "source": [
    "backtest = run_algorithm(start=start,\n",
    "                         end=end,\n",
    "                         initialize=initialize,\n",
    "                         before_trading_start=before_trading_start,\n",
    "                         bundle='quandl',\n",
    "                         capital_base=capital_base)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract pyfolio Inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `extract_rets_pos_txn_from_zipline` utility provided by `pyfolio` extracts the data used to compute performance metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:10.583537Z",
     "start_time": "2021-04-15T19:48:09.696041Z"
    }
   },
   "outputs": [],
   "source": [
    "returns, positions, transactions = extract_rets_pos_txn_from_zipline(backtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist Results for use with `pyfolio`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:10.928631Z",
     "start_time": "2021-04-15T19:48:10.584600Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    store.put('backtest/equal_weight', backtest)\n",
    "    store.put('returns/equal_weight', returns)\n",
    "    store.put('positions/equal_weight', positions)\n",
    "    store.put('transactions/equal_weight', transactions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:11.342373Z",
     "start_time": "2021-04-15T19:48:10.929577Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes= plt.subplots(nrows=2, figsize=(14,6))\n",
    "returns.add(1).cumprod().sub(1).plot(ax=axes[0], title='Cumulative Returns')\n",
    "transactions.groupby(transactions.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1], title='Cumulative Transactions')\n",
    "fig.tight_layout()\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:11.346118Z",
     "start_time": "2021-04-15T19:48:11.343362Z"
    }
   },
   "outputs": [],
   "source": [
    "positions.index = positions.index.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:13.091940Z",
     "start_time": "2021-04-15T19:48:11.347306Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GpUuXePHFF7tU4Add+0YlRGtobq25PLzWJk2iui5t/9ZyToi2Js9NnV+7BX92dnYMHTpU+ezj40NwcHCz1hUYGEhycjJqtZoLFy5oVeuXlZVFXl4eM2fOZN++fcTExHDixAmWL1/Onj17gKoE8LNmzeLWrVuUl5czefJkJkyYAFSNtvn+++/z9ddf061bNyZMmMCUKVM0tpGamkpcXBweHh4sWrRImR4dHc2hQ4fYs2ePEmCmpqZy5MgRjaTx169fZ+zYsSQmJnL//fdTVlaGv78/0dHRDBs2DBsbG1588UXCw8MB+Pjjj7lx4wazZs0iOTmZP//8k6eeeoo+ffoQGxvLyJEjm3V8hRCimjyMthw5lkK0Hul2IUTd2i34qyttQ3MlJycDVcFaeno6Y8aMaXSZxMREpd9c//79Wbx4MZ988onGPPfccw/Jycn06NGD4uJixowZg7u7O3379iU1NZX//ve/StPQixcv1rkdb29vjYCuoqKCrKws+vfvz759+3jooYfqLaOxsTFz5swhKiqKTz75hE8++QQnJyeGDRsGVCV837lzJ8HBwbWSzwcFBdG7d2+OHDkCwOTJk4mMjOSRRx5p9NgIIYQQdekMtZW60LdQtD75WwpRN51r9pmdnU1MTAympqbY29tz5swZ1qxZw8qVKzEyMmLq1KkAjB49mtWrV2NhYYGTkxO5ubnEx8eTn5+Pn58f48aNY+fOnURGRmJnZwdU1RAuXLgQAwMD9PX1lYDJwsICoFYzz5oDsJSWlmqkjfj888+Jj49XljE3N9dq/3JychgyZAje3t5kZGQ0GPxBVfCYkpLCRx99RHJyMlu3blW+6969O8899xxJSUm88cYbDa5nwIABXLlyhaKiIu655x6tyiqEEELU1BkeqDvDPrS1+vqB1WwiePs80nxQCN3UbsHf7SN3Tps2DQ8PDyIjI0lKSsLKyorZs2c3aZ1z587VGOzFxMSE1NRUIiIiOHXqFKWlpdja2pKSkoK9vb1W6/zvf/9LcHAwBQUFhIWFKTn8zpw5w44dO/j2228xMzPj7bffrnM00dulp6fj4+PDk08+yfLlyykrK0NfX7/BZd566y28vb157733lNQT1SZNmoSvr2+j6SQAHnjgAQ4ePIinp2ej8wpRH2lKI0THos3AV/KgLhqizfkh55AQHYNONfs8fvw4FhYWShDl6+vL5s2bm70NLy8vEhISCAsLIyUlRUndUFRUVKuZZH369+/PV199RWFhIa+++iqenp7cfffdlJaWYmBgQGpqKjt37uStt95i06ZNDa6rtLSUPXv2MH/+fIyNjRk2bBg//fRTo+kXfvjhB+655x7+/e9/1/rO2NgYPz8/PvvsM3r27NngeszNzblw4UKj+yxEQyTg0301H/blgUzIOSCEEKKazjX7VKlUdU7X09PTaHZZUlLS6LoMDQ1xdXVl165dZGZmkpKSAlQFnteuXWtSufr27cuQIUPYv38/Xl5e9O3bl6effhqAp556ivnzGx+q9YcffuD69ev4+voCcPPmTXr27Nlg8FdYWMj69evZsmULU6ZMIS8vr1Zy9xdeeAF/f3+NvIR1KSkpaTRA7MyakvZBHpZERybnrxBCCCHqolPBn7W1NWq1moKCAiwtLcnIyFC+GzBgALt37wbg6NGjqNXqWsv36tWL4uJijWkBAQGEhITg4uKiNJm0trZm+/btjZbn/Pnz9OnTh549e/Lnn39y8OBBgoKCAHjyySf5+eef+fvf/84vv/yiVZPPjIwMoqOjGT16NAA3btzAw8ODmzdv1rvM4sWLCQkJoV+/foSHhxMVFcXGjRs1guQ+ffrg5eXFli1bGD9+fL3rOn36NF5eXo2WsyZthnVvj5ogbQO5mg/B8kAsROuR/j5CCNG5dIYBnkRtOtPnz83NjdDQUKKioggODsbU1BRnZ2dOnjwJgKenJ2lpafj5+eHo6FhnsGVjY4Oenh6+vr74+/sTFBSEg4MDxsbGGrViI0aMIDY2lsrKSlQqFYcPH2bmzJlcvXqV77//npUrV5KRkUF+fj5LlixBpVJRWVnJSy+9hI2NDQDBwcGEhoaSlJSEkZGRRiqHuty8eZMff/yRqKgoZZqRkRHOzs58//33AGzdupWsrCzl+zlz5vDf//6Xv//970BVwvbNmzezbds2xo0bp7H+l156iY0bN9a7/bKyMn7//XccHBwaLOftdPVClwdLIXSLXJMdj/TfFUI0RO4LnZOqsrKysr0LUZ+cnByNAVyao7CwkClTpigpGapFR0fj7u6Oq6trSxS1TnXl7mtLNbf/7bffcvTo0SYPonOn6qs57Co3FHm4EkKIjqOr/2YJcac663PP41GLW2W9exY03m2spelUs8+Wtm3bNlasWEF4eHitNA4hISEcOnSoVbffs2dPsrOziYiIaLRmsKWtW7eOzz//XBnZs7y8nJdeeqlNywCd68Jvjq6+/6Lz/hCKOyejcN65lh7cSK5RIe6MXEO6T6dr/oQQQgghqjWnv7cQQtypzlTz163xWdqHnZ0dfn5+yr+1a9c2e12BgYEAqNVqvvrqK62WycrKYtWqVQDs27ePcePG8cADD/D1119rzLd06VJGjx7N6NGj2bFjhzJ97ty5eHp6Mnr0aObPn09ZWVmtbaSmpvLwww8TERGhMT06Oho3NzeN0U2r5/Xz88Pb21sjBca3336LjY0N+fn5yrSCggL8/PxwcnIC4MSJE4SHh2u170IIIURruPDrwTr/aetexwe1+ieEEKJuOtvss648gM2VnJwMwNmzZ0lPT2fMmDGNLpOYmEhCQgJQletv8eLFfPLJJxrz7N69m2PHjrFt2zZKS0uZPHkyI0eOxNjYGF9fX5YtWwZUBYJffvklEydOrLUdb29vjT6BFRUVZGVl0b9/f/bt28dDDz1Ua96LFy/i4+ODu7s7d999N+np6Tg7O7Njxw5mzZoFgKWlJWlpaUrwZ2Njw/nz5zl37hx/+ctfmnL4hBDtSEbRFJ1JS5+/0qxa6CrJtyp0lc7W/NUnOzsbLy8vJkyYQHR0NNOmTQNg5cqVfPzxx8p8o0ePVtJBVAdA8fHx7N+/Hz8/P9atW8fEiRM5fvy4skxgYCB5eXmcOnUKfX19JRG8hYUFtra2tfoN/uc//2HEiBF0794dIyMjbG1tyc7OBuDxxx9HpVKhUqn461//SmFhoVb7l5OTw5AhQ5gwYYJGqouazM3NsbS05Ny5cxQXF3Pw4EEWLVpU7/zVnnjiiUbnEZ1bfW/dm/LmXbQtqdEQon4ug6yVf0LoErlvC12lszV/t6eCmDZtGh4eHkRGRpKUlISVlVWTR66cO3euxuihJiYmpKamEhERwalTpygtLcXW1paUlBTs7e0bXZ+trS2rVq3ixRdf5ObNm+Tk5DB48GCNecrKykhLS6vVtLM+6enp+Pj48OSTT7J8+XLKysrQ19fXmOfMmTOcOXMGS0tLsrKycHNzY+DAgfTp04ejR4/WW3YHBwc++ugjXnnlFa3KIjof+RESHVFDtTsyOqMQQtRNah9FXXQ2+Kur2efx48exsLBQcvz5+vpq9H1rKi8vLxISEggLCyMlJUXJBVhUVKTU+jXkscce49dffyUwMBAzMzOGDx+Onp6exjzvvvsuLi4uuLi4NLq+0tJS9uzZw/z58zE2NmbYsGH89NNPjBo1CoAdO3Zw4MABevToQVRUFH369CEjI4MXXngBqGoWmp6eXm/wZ25uzoULFxoth2hfcrNuX9LMUvc0FMhJkCdE65PfpY6p5t9KmkiLajob/NVHpVLVOV1PT09jgJSSkpJG12VoaIirqyu7du0iMzOTlJQUoCrwvHbtmlblmT59OtOnTweqahZrJp9ftWoVly5dUgaOacwPP/zA9evX8fX1BaoSw/fs2VMJ/m7vH3j58mV+/vlnTp48iUql4tatW6hUKsLCwuo8TiUlJRgYGGhVFtF+5Ie1fcnxF0LoiuY0yW+Ne5jcFzs+CfhEtQ4V/FlbW6NWqykoKMDS0lKj/9qAAQPYvXs3AEePHlX6+9XUq1cviouLNaYFBAQQEhKCi4sLffr0Ubazffv2Rstz69Ytrl69iqmpKXl5eZw4cYJHH30UgC+//JIff/yRdevW1eorWJ+MjAyio6MZPXo0ADdu3MDDw4ObN2/WOf8333zD2LFjiYqKUqZNnjyZAwcO1FnTePr0aYYMGaJVWYSoT30PI/JwILoiXW12Km/5Owdt7qtSKyeEaAqdDf5u7/Pn5uZGaGgoUVFRBAcHY2pqirOzMydPngTA09OTtLQ0/Pz8cHR01KiBq2ZjY4Oenh6+vr74+/sTFBSEg4MDxsbGSpNPgBEjRhAbG0tlZSUqlYrDhw8zc+ZMrl69yvfff8/KlSvJyMigvLycSZMmAWBsbMzSpUvp3r3qkL7zzjv85S9/4bnnngPgqaeeYubMmfXu782bN/nxxx81AjkjIyOcnZ35/vvv61wmIyOjVv+9p59+mq+++qrO4C8nJ0epRRSadPUBThfJw4UQ/6c97xEN1Qq5yHXaZcg9WQjRFB06yXtOTo7GAC7NUVhYyJQpU8jMzNSooYuOjsbd3R1XV9eWKGqdUlNTOXLkiEZTzpbm5OREbm6ukopi06ZNSoAqRFejTRMqeZASQgghRE2dKcl7l44Ctm3bxooVKwgPD6/VNDMkJIRDhw616vZ79uxJdnY2ERERLFq0qEXXXVBQwKxZszA3Nwfg3LlzzJ07t9UDvztNGSAP3qI1yfklhBB3RpoUi9tJ66mORSeDPzs7O4YOHap89vHxITg4uNZ8Dz30kEYS9LoEBgaSnJyMWq0mNzdXI8H72LFjGTt2bK1lsrKyyMvLY+bMmXz66ad8+eWX6OnpYWZmRkxMDAMGDABg6dKl7NmzB4AZM2bg7e0NVKVimDNnDn/++ScPPPAAcXFx9OjRQ2MbqampxMXF4eHhoRH4RUdH880337Bnzx4lIP300085efIkMTExAGzfvp309HTWrl3LypUr2bx5M2ZmZty6dYs33ngDDw8PvvvuO/7880/c3d0B+OKLLxg5cmSDx6olyMO1EKI1yWisQrQveaAXt5NzomPRyeCvrjQPzZWcnAzA2bNnSU9P1wj+6pOYmEhCQgJQFYimpKRgaGjIpk2bWLp0Ke+//z67d+/m2LFjbNu2TWlSOXLkSIyNjVm2bBlBQUH4+PiwYMECtmzZwsSJE2tt5/bROysqKsjKyqJ///7s27dPCWyff/55xo8fz4EDBxgyZAjvv/8+SUlJynJBQUFMnTqV/Px8Jk6cyN69ewkKCqJ3794cOXIEqBoIJjIykkceeaT5B7MLko707UeOfed0p39XOReEEEKI5tNuGEodkZ2djZeXFxMmTCA6Oppp06YBsHLlSj7++GNlvtGjRyujfTo5OQEQHx/P/v378fPzY926dUycOJHjx48rywQGBpKXl8epU6fQ19dX8vw9/PDDGBoaAjB8+HDOnz8PwH/+8x9GjBhB9+7dMTIywtbWluzsbCorK/n555/x9PQEYNy4cezatUur/cvJyWHIkCFMmDBBYyTT7t2788477xAVFcXSpUsZP3489913X63lBw0aRPfu3bl8+XKt7wYMGMCVK1coKirSqiyiyr2ODyr/RNuSY985dZW/6/783+r8p6su/HpQ458QQojOSSdr/m4f6XPatGl4eHgQGRlJUlISVlZWzJ49u0nrnDt3rsbgMCYmJqSmphIREcGpU6coLS3F1taWlJSUepOkb9myRWk6aWtry6pVq3jxxRe5efMmOTk5DB48mMuXL9O7d2+lb12/fv0oLCzUqozp6en4+Pjw5JNPsnz5csrKytDX1wfgwQcfZNCgQfzrX/8iMzOzzuUPHTqESqWqN0H9Aw88wMGDB5XAVAghROvoaM2gOnswLhrX0MuJjnY+CyHqp5PBX13NPo8fP46FhYWSwsHX15fNmzc3exteXl4kJCQQFhZGSkqKkuqhqKiozuApLS2NI0eOsGHDBgAee+wxfv31VwIDAzEzM2P48OHo6enVua36EtPXVFpayp49e5g/fz7GxsYMGzaMn376SUnNUFxczJEjRygvL+fSpUv069dPWXbdunVs376dXr168f7779e7PXNzcy5cuNBoWYQQXVtjNVTyICi6ss464Eln2hchRP10MvirT31BjZ6eHhUVFcrnkpKSRtdlaGiIq6sru3btIjMzk5SUFKAq8Lx27ZrGvP/6179YvXo1GzZs0Bi4Zfr06UyfPh2oqlm8//77MTU15erVq5SXl9O9e3fOnz/Pvffe22h5fvjhB65fv46vry9QlfevZ8+eSvC3cuVKfH19MTc3JyYmhn/84x/KstV9/hpTUlJCz549G52vPclgDqI1ddaHtpYmx6ZtaNP/Ue6JukeuDyFER9Zhgj9ra2vUajUFBQVYWlpq9IkbMGAAu3fvBuDo0aNKf7+aevXqRXFxsca0gIAAQkJCcHFxoU+fPsp2tm/frsxz7NgxFixYQGJiopI2AeDWrVtcvXoVU1NT8vLyOHHiBI8++igqlYqHHnqIb775Bh8fH7Zu3aqMuNmQjIwMoqOjGT16NAA3btzAw8ODmzdvUlBQwO7du0lLS0NfX5+UlBR++uknHn30Ua2PH8Dp06fx8vJq0jJtTR5s2k5z+x915Aeftiq75BMU2tDmHOiq58mdDgzU3KC5+r7Yke9zQrQnaT6s+3Qy+Lu9z5+bmxuhoaFERUURHByMqakpzs7OnDx5EgBPT0/S0tLw8/PD0dFRaRpak42NDXp6evj6+uLv709QUBAODg4YGxsrTT4BRowYQWxsLJWVlahUKuLi4rhx4wavv/46AP3792f16tWUl5czadIkAIyNjVm6dKnSz2/evHm88cYbvP/++9jZ2REQENDg/t68eZMff/yRqKgoZZqRkRHOzs58//33rF+/nvnz52NgYADAO++8w5tvvsm2bdu0PqZlZWX8/vvvODg4aL3M7bQdBOBOHla0/cGWkSDvXGe7CWsTzLbVPss5KTqa26+f9r4/3Ok11NzlLW9cARr+vZPrW4j6tfe9QzROVVlZWdnehWiOnJwcjQFcmqOwsJApU6aQmZmpkeQ9Ojoad3d3XF1dW6KodUpNTeXIkSMaqR5acxvffvstR48ebfJAOULcri1eAog7I81bRVckAZvQVVIb1vE9HrW4Vda7Z8H8VllvQ3Sy5q8tbNu2jRUrVhAeHq4R+AGEhIRw6NChVt1+z549yc7OJiIiQiPJe0tZt24dn3/+uTKyZ3l5OS+99FKLb0d0Pbr6ENXU4el1dT9agjxMiK6oM1/TomOTe7LQJR225k+I9tSc/nJy8xdCCCGE6Hik5q8V2NnZMXToUOWzj48PwcHBzVpXYGAgycnJqNVqcnNzGTNmTKPLZGVlkZeXx8yZM/n888/ZtGkT3bp1w8jIiPfee4/BgwcDEBcXx549e6ioqODRRx8lIiIClUrF3LlzOXLkCPr6+jg6OhIVFaXk6KuWmppKXFwcHh4eLFq0iJycHGbMmIGFhQUVFRWYm5sTHx+Pubm5RpPNiooK5s+fT7du3Th+/DiLFy/Gzs6O8vJyXFxcePfdd5U+kv7+/rz33nv8/vvvrFixAmtra9asWcOGDRswNDRk/PjxzTqmuqxmIGZ540qbvP2VQE4ITdLkrmXV94JJ7j1CCCHuhM4Ef3Xl9muu5ORkAM6ePUt6erpWwV9iYiIJCQkAjBkzhgkTJgCwa9cuFi9ezMcff8zBgwc5ePCgMhroxIkT+eWXX3jooYfw9fVl2bJlQFXahy+//JKJEyfW2o63t7dGPz8XFxel32J8fDwbN27ktddeU76vrKzknXfeoby8nKVLl/Lee+9x8OBB7OzsyMvLY+DAgeTm5uLn58eNGzc4c+YMtra22NvbY25uzieffALA+PHjmTBhQqcM/jrDw5D0oxMdnZybLasz3Nd0la71iZXRgYUQbUlngr/6ZGdnExMTg6mpKfb29pw5c4Y1a9awcuVKjIyMlPx2o0ePZvXq1VhYWODk5ERubi7x8fHk5+fj5+fHuHHj2LlzJ5GRkdjZ2QFVNYQLFy7EwMAAfX19Jbm7sbGxsv2bN28q+QVVKhWlpaWUlZVRWVlJWVkZd999NwCPP/64ssxf//pXCgsLm7SflZWVFBcXY2lpqTF90aJFXLlyhRUrVtCtWzcefPBB9uzZw6RJk8jNzSUwMJCtW7cCcPjwYR544IE6k80bGhoyYMAADh8+zF//+tcmlU00TXMeLOSHXYiuQdcCj66ooePeHqke5P4vhGhLOhP83Z7eYdq0aXh4eBAZGUlSUhJWVlZNHqly7ty5GiOCmpiYkJqaSkREBKdOnaK0tBRbW1tSUlKwt7fXWHbjxo18+umnlJWVkZSUBICTkxMPPfQQjz32GJWVlUyePJlBgwZpLFdWVkZaWhoRERFalXH//v34+flx5coVDA0NmTNnjvJdeno61tbWrF+/Xkkj4eTkxPvvvw9Abm4ur776Kunp6Vy/fp3c3FwefLD+HxEHBwf2798vwV8raG7OPCFE1yIBn26Tv48QorPTmeCvrmafx48fx8LCQsnb5+vry+bNm5u9DS8vLxISEggLCyMlJUXJ71dUVKTU+lWbNGkSkyZN4quvvuLDDz8kNjaW33//nfz8fPbs2QPASy+9xL59+xgxYoSy3LvvvouLiwsuLi5alalms8+1a9cSFxen5Pt74IEH+O233zh8+DDOzs4AWFhYUFZWRlFREb/99hvW1tY4Ojpy+PBhcnNzmTx5cr3bMjc357ffJEhpDfLAIIQQQoimkv7Soq3pTPBXn+oml7fT09OjoqJC+VxSUtLougwNDXF1dWXXrl1kZmaSkpICVAWe165dq3MZHx8fFi5cCMC3337LsGHD6NWrF1CVfP7//b//pwR/q1at4tKlS6xatUrr/avJw8ODWbNmKZ+tra157bXXmD17Nh9//DFDhgwBYPjw4XzzzTfcc889qFQqhg8fzsGDBzl8+DDDhw+vd/0lJSVKonghhBBCtKyaD/Ly4C60IeeJaGvdGp+l/VhbW6NWqykoKAAgIyND+W7AgAEcO3YMgKNHj6JWq2st36tXL4qLizWmBQQEEB0djaOjI3369FG28/vvvyvznD59Wvn/3bt3Y2VlBcBf/vIX9u3bR3l5OWVlZezbt09p9vnll1/y448/snz58lp5A7V14MCBWn3+HnzwQd59912mTZvGuXPnlGnr1q1TAr3hw4ezbds27rnnHnr37l3v+k+fPq0xoqoQQoimu/DrwTr/CXGv44PKPyGE0EU6U/N3e58/Nzc3QkNDiYqKIjg4GFNTU5ydnTl58iQAnp6epKWl4efnh6Ojo9I0tCYbGxv09PTw9fXF39+foKAgHBwcMDY2Vpp8AowYMYLY2FgqKytRqVRs2LCBvXv30r17d3r37k1sbKyyzZ9//pkxY8agUqlwc3PD3d0dgHfeeYe//OUvPPfccwA89dRTzJw5s9H9ru7zV1lZyV133UV0dHSteZ544gkuXbrEyy+/zMaNG3nwwQdZvHgxTk5OANx7771UVFQon+tz8OBBXn311UbLJIQQon7yYC9a0u19xi1vXFH+X841IURL61BJ3nNycjQGcGmOwsJCpkyZQmZmpkYNXXR0NO7u7ri6urZEUetUM3dfW6h5vI4dO8ann37K0qVL22TbQgghtFdfzaE8/AshRPuTJO8d1LZt21ixYgXh4eG1mmaGhIRw6NChVt1+z549yc7OJiIigkWLFrXqtnbs2MGqVauUUUwvX77M66+/3qrbFM2n7WihMrCMqI/kiuzYOtvfRfq+CSHEnZs/fz67d+/G3Nyc9PT0Wt9v376djz76CKjq7rZw4UJsbW0bXGebBn92dnYafc58fHwIDg7WevmHHnqIhx56CKjK0ZecnIxarSY3N1erRO7GxsYEBATwzDPPKNO+/vprXn/9dbZs2YKHh4cy/fr16zzzzDM89dRTSk3d3r17iYuLo6KiAiMjI5YsWaL0B6yWmppKXFwcHh4eLFq0iJycHGbMmIGFhQUVFRVYWFgwZ84csrKySE1NVRLLr1mzhi1btvDtt98C8N1337F582ZWr16Nu7s7W7Zs0RiRtHo7/fr148aNG9x33328+uqrSqqHX3/9lT///FM5AbZs2SLBnw6ToE531fcQe3uw1d4PuO29fSFq6qjnY3vk+RNCiPr4+/szefJk3nzzzTq/t7CwYMOGDZiYmLBnzx4iIyP58ssvG1xnmwZ/daVzaK7k5GQAzp49S3p6ulbBX2JiohJsQVWAt379eoYNG1Zr3vfff5+//e1vGtMWLlxIQkICgwYNYuPGjXz44YcsWbKk1rLe3t4aTTtrpnOIj49n48aNTJ48WWOe3NxcjI2NuXjxIubm5o3m7Lt9Oz///DOzZs3is88+Y9CgQbz55psYGRkp806YMIHExMQ6+xTeKRmmWHRm9Z3Dcm6Lhmjz0kDOId0jQV/H0tBLOHk2EZ3BiBEj6hzUslrNWGH48OGcP3++0XXqRLPP7OxsYmJiMDU1xd7enjNnzrBmzRpWrlyJkZERU6dOBWD06NGsXr0aCwsLnJycyM3NJT4+nvz8fPz8/Bg3bhw7d+4kMjISOzs7oKqGcOHChRgYGKCvr69Re/bBBx/w8ssv88knn2iU58iRI1y8eBE3NzeOHDmi8d3169eV/957771N2s/KykqKi4uxtLTEzMyMu+66i99//x0rKysuXLjA008/TW5uLk8++SS5ublNSmr/8MMP8+yzz/LFF1/w1ltv1frexcWF8PBwysvLlYTxLUVuokIIoamjvTTQtuk5tGyAdPt2JfgSTdHQ9aSr15oQNX3xxRd88cUXyufnnntOGTyyqbZs2cLIkSMbna9Ng7/bR/ScNm0aHh4eREZGkpSUhJWVVZMCHoC5c+dqDAJjYmJCamoqERERnDp1itLSUmxtbUlJSVH6vwEcO3aM8+fP88QTT2gEfxUVFcTGxhIXF8fevXs1trVo0SKCg4MxMDDA2NhY64Tz1SN6XrlyBUNDQ+bMmQOgBLC3bt3CysqK4cOH88MPPzBq1ChOnDiBo6Njk46Fvb29UiN6u27dumFlZUVeXh4ODg5NWq8QQojOrb2Crq4a7NUMervqMejKpFZSVLuTYK+mn3/+mS1btrBp06ZG5233Zp/Hjx/HwsJCSdXg6+urdVBVFy8vLxISEggLCyMlJUVJ6VBUVKTU+lVUVLB48WIWL649cs+mTZsYOXIk/fv3r/XdunXrWLt2LcOGDSMxMZHFixdrNXBLzWafa9euJS4ujqioKB588EEOHjzIrVu3GD58OI6Ojvzzn//k2LFjDBw4sMkJ2RsbuNXMzIwLFy40aZ1CCFFTc/PZyQONEP9HAr6uTe6HoiXl5eXx9ttv89FHH2Fqatro/DrR7FOlUtU5XU9Pj4qKCuVzSUlJo+syNDTE1dWVXbt2kZmZSUpKClAVeF67dg2A4uJi/v3vfzNlyhSgKjCcPn06H374Ibm5uRw4cIDPP/+c4uJiysrKMDIy4qWXXiIvL0/pH+jt7c3LL7/c5H318PBg1qxZQFXN3/r166moqODZZ5/F2NiYkpISfvnll0b7+9Xl2LFjStL5upSWltKzZ88mr1cIIarJQ4t26mtGKQ/9QgghWsq5c+eYNWsWcXFxDBw4UKtl2j34s7a2Rq1WU1BQgKWlJRkZGcp3AwYMYPfu3QAcPXq0zg6PvXr1ori4WGNaQEAAISEhuLi40KdPH2U727dvB+Cuu+4iJydHmf/5558nLCwMR0dH4uPjlenVeflCQ0MpLy/n2rVrnDp1ioEDB/LTTz81GGjV58CBA1haWgIwePBgLly4wP79+3nnnXeAqhFRk5OTmTdvXpPW+8svv7B582Y+++yzeuc5ffo0gwcPbnKZhRBCNI0EeaIl6NqowqLjaqzVhpxbumnOnDn88ssvXL58mZEjRzJr1izKy8uBqsEc//nPf3LlyhXeffddoKriLDU1tcF1tmufPzc3N0JDQ4mKiiI4OBhTU1OcnZ05efIkAJ6enqSlpeHn54ejo6PSNLQmGxsb9PT08PX1xd/fn6CgIBwcHDA2NlaafELVaDmxsbFUVlbWW9PYkO7duxMdHc1rr72GSqXCxMSEmJgYrZat7vNXWVnJXXfdpYy4qVKpGDZsGNeuXUNfXx+oGqnniy++wMnJSWMdvr6+Sm7CZ555BhsbG3bs2MGBAwf43//+h4WFBf/4xz/qDUj/+OMPDAwMmjxITXuTt+cdlyStbhrpAyRE19TQCLByvxQtRc6ljmn58uUNfr9o0aIm5w5XVTbWUayN5eTkaAzg0hyFhYVMmTKFzMxMjWTu0dHRuLu74+rq2hJFrVN1bWHNNA7tpeZoqevWraNXr14EBAS0d7GEEKLD6crBeWdOT9GcPqyd7RgIIRr3eFTtcUJawp4F81tlvQ1p92afLW3btm2sWLGC8PBwjcAPICQkhEOHDrXq9nv27El2djYRERFNjsRbUmxsLFlZWbz44otAVVPXmrWuQgghtNfVAr6aOnOw05n3TbS+ul4eyDkldJ3O1fwJIcSdaChfWVd+gBeivTSn1lRq5IQQukRq/tqAnZ0dQ4cOVT77+PgQHBzcrHUFBgaSnJyMWq0mNzeXMWPGNLpMVlYWeXl5zJw5k9TUVOLi4ujbty8AkydPVppPTp06lUOHDuHs7FxnU9X33nuP1NRUcnNza31XvV4PDw+llvDw4cPExsbyxx9/oFKpcHZ25u2338bQ0JA9e/bwwQcfcPPmTSorK3niiSd48803NZp3Vvvf//7Hc889R35+PtnZ2QDMmzePjz/+uOkHUIgORAI8IXRLc67JAqM+d7S8EEKIuuls8FdXTsDmqk58fvbsWdLT07UK/hITE0lISFA+e3t719mP7+WXX+bmzZt88cUXtb779ddfuXr1aoPbqbneP/74g9dff53ly5fj5OREZWUl33zzDcXFxZw5c4b33nuPNWvWMGjQIMrLy+vcZrXq4+fu7g5U5fi79957OXDgAM7Ozo3uvxBCiP/T1JooqYW6MxLwCSFE69DZ4K8+2dnZxMTEYGpqir29PWfOnGHNmjW1ar9Gjx7N6tWrsbCwwMnJidzcXOLj48nPz8fPz49x48axc+dOIiMjsbOzA6pqCBcuXIiBgQH6+vpKUviGPPLIIxppI6rdunWLuLg44uPjycrK0mrfNm7cyNixY5WRPlUqFV5eXgDExcUREhKijObZvXt3Jk2apNV6q3l4ePDVV1+1ePDXUDO7+rTVD3tLDpPdlQd8EKKru5N7hzaBowSLQnQcTR3N+vbnpI76DKHNCOzyrKT7dDb4uz0txLRp0/Dw8CAyMpKkpCSsrKyYPXt2k9Y5d+5cjZFETUxMSE1NJSIiglOnTlFaWoqtrS0pKSnY29trLLtz50727dvHwIEDmT9/Pv37929wWxs2bMDDw6NJqRVOnjzJ2LFj6/3upZde0npddXF0dOSDDz64o3XURZcv7pZ8oNLl/RRC6C4J7IToXJp6Tev680N9L8pvn+6ixX7r+r4KHQ7+6mr2efz4cSwsLJR8f76+vmzevLnZ2/Dy8iIhIYGwsDBSUlKUvIBFRUUatX5PPPEEo0ePpkePHnz++ee8+eabDSZTLyws5Ouvv2b9+vXNLltrMDMz48KFC+1dDKEjtE34KkmGhRDVmlOD0VlqPYT25G/esdT3u377dKnV6xx0NvirT30J2vX09KioqFA+l5SUNLouQ0NDXF1d2bVrF5mZmaSkpABVgee1a9eU+UxNTZX/f/bZZ1m2bFmD6z1+/DgFBQU8/fTTANy8eZOnnnqKb7/9tsHlBg8ezNGjR3nyySfr/O7IkSPY2to2ul/1KSkpwcDAoNnLi85F2yBOgj0hmq6pzcI6iuY88HWGh0RtmruJ/yPHpeW1Zr5Nbdctf9fOoUMFf9bW1qjVagoKCrC0tCQjI0P5bsCAAezevRuAo0ePolaray3fq1cviouLNaYFBAQQEhKCi4sLffr0Ubazfft2ZZ4LFy4ozTe/++47pd9dfUaNGsVPP/2kfHZycmo08IP/G0V01KhRDBs2DIC0tDRcXV2ZOnUqs2bNwtnZmYEDB1JRUUFSUpKSx08bp0+fZsiQIVrPL+ontWFCtA9tB15p72uyvbcvWpY89Ir21pr3FLlfdS06G/zd3ufPzc2N0NBQoqKiCA4OxtTUFGdnZ06ePAmAp6cnaWlp+Pn54ejoqDQNrcnGxgY9PT18fX3x9/cnKCgIBwcHjI2NlSafACNGjCA2NpbKykpUKhXr16/nu+++Q09PDxMTExYv/r9cHxMnTuS3337jxo0bjBw5kkWLFuHm5tasfb777rtZvnw5sbGxXLx4kW7dujFixAiefvpp7rnnHt566y3mzp3LzZs3UalUPP7448qyH374IUlJScrn6vQONeXk5DBq1KhmlU1okhulEO1Drr26SX7L1tWatS6dUUd5SSNEV9Shk7zn5ORoDODSHIWFhUyZMoXMzEy6deumTI+Ojsbd3R1XV9eWKGqdUlNTOXLkSJ0pJFqKu7s7W7ZswczMjEmTJpGQkICJiUmrbU8IIYSoT0N9wbTpTyR9yUR7kPNOSJL3TmLbtm2sWLGC8PBwjcAPICQkhEOHDrXq9nv27El2djYRERFKkveWUp3kvaysjG7dunHp0iVefPHFDhf4ydtW0d7ao4N7Q2/N5ToQHVlD15A215c8dIvmuNOuGrpw3snzkGgpOh382dnZMXToUOWzj48PwcHByueHHnqIhx56SKt1BQYGkpycjFqtJjc3lzFjxjB27Nh6UyvcfffdVFZWsmrVKmbOnElqaipxcXH07dsX+L/+eQBLly5lz549AMyYMQNvb28Azpw5w5w5c/jzzz954IEHiIuLo0ePHso2vL29+d///kdcXByAEgAePnyY2NhY/vjjD1QqFc7Ozrz99ttkZmbWWVPo7u5Or169lAD2nXfe4e677wbg+vXr9OnThxMnTpCVlVXnYDK6TG5wnZsu54hsr+2BnPdCCNGSOsM9tTPsg9ANOh381ZXuobmSk5MBOHv2LOnp6YwZM6bRZRITE0lISFA+e3t71wq8du/ezbFjx9i2bRulpaVMnjyZkSNHYmxszLJlywgKCsLHx4cFCxawZcsWJk6cWGs7Ndf7xx9/8Prrr7N8+XKcnJyorKzkm2++qTVQze2SkpJqJaVPS0tTEsbb2Nhw/vx5zp07x1/+8pdG912ItqALb1N1UUcZTltqKIUQQoiORaeDv/pkZ2cTExODqakp9vb2nDlzhjVr1rBy5UqMjIyYOnUqAKNHj2b16tVYWFjg5OREbm4u8fHx5Ofn4+fnx7hx49i5cyeRkZHY2dkBVTWECxcuxMDAAH19/VoB1e3+85//MGLECLp370737t2xtbUlOzubZ555hp9//pn4+HgAxo0bx6pVq+oM/mrauHEjY8eOVYI2lUqFl5fXnR4yoCpfYUZGBq+88kqLrE8IaYbSOnQ54KtJ/uais6l+8dJRrkHRNbXXC8KmttaR60g36XTwd/uIn9OmTcPDw4PIyEiSkpKwsrJi9uzZTVrn3LlzNQaJMTExITU1lYiICE6dOkVpaSm2trakpKRgb2+vsezOnTvZt28fAwcOZP78+fTv3x9bW1tWrVrFiy++yM2bN8nJyWHw4MFcvnyZ3r1707171SHu168fhYWFjZbv5MmT9TZFbcgLL7xAt27d6NGjB19++WWd8zg4OPDRRx/pRPAnOZO0o+s1K7pQBiGEaCnyGyQ6gvY6T+X66Bx0Ovirq9nn8ePHsbCwUFI5+Pr6snnz5mZvw8vLi4SEBMLCwkhJSVFSPhQVFWnU+j3xxBOMHj2aHj168Pnnn/Pmm2/y2Wef8dhjj/Hrr78SGBiImZkZw4cPR09Pr85t1ZegviXU1ezzdubm5ly4cKHVytAUcgPRjgRXQgjRdTWnXzTIb2xXousviYXu0engrz71BVF6enpUVFQon0tKShpdl6GhIa6uruzatYvMzExSUlKAqsDz2rVrynympqbK/z/77LMsW7ZM+Tx9+nSmT58OVNUs3n///ZiamnL16lXKy8vp3r0758+fVxLFN2Tw4MEcPXq0VQZmKSkpwcDAoMXXK4QQ7UWGYBedmZzPojES4Imm6tb4LLrF2toatVpNQUEBABkZGcp3AwYM4NixYwAcPXoUtVpda/levXrVGjwlICCA6OhoHB0d6dOnj7Kd33//XZmnZo3Zd999x6BBgwC4desWly9fBiAvL48TJ07w6KOPolKpeOihh/jmm28A2Lp1K+7u7o3u3+TJk9m2bZtGmom0tDSKiooaXbYxp0+fZsiQIXe8HtE8F349qPwTQrQMl0HWGv+EEEIIUT+drvm7vc+fm5sboaGhREVFERwcjKmpKc7Ozpw8eRIAT09P0tLS8PPzw9HRUWkaWpONjQ16enr4+vri7+9PUFAQDg4OGBsbK00+AUaMGEFsbCyVlZWoVCrWr1/Pd999h56eHiYmJixeXJXssby8nEmTJgFgbGzM0qVLlX5+8+bN44033uD999/Hzs5OSQ3RkLvvvpvly5cTGxvLxYsX6datGyNGjODpp58GqoLIrKwsZf6mNHnNyclh1KhRWs8vNGkbtNX3Fk7ezglRvzvNwyWaTtsmhRJUi/bWUUZAFqIjUFVWVla2dyHuRE5OjsYALs1RWFjIlClTyMzM1Ej2Hh0djbu7O66uri1R1DqlpqbWmbuvpVSPclqdhmLTpk1KcCqEEEKIjqetg6H6Xn7KSxrRVTwetbhV1rtnwfxWWW9DunwUsG3bNlasWEF4eLhG4AcQEhKi0fyyNfTs2ZPs7GwiIiKUJO8toaCggFmzZmFubg7AuXPnmDt3rgR+QgjRgXXmkZKldkd7bX18dCnIk/NEiDujUzV/dnZ2DB06VPns4+NDcHBws9YVGBhIcnIyarWa3NxcrZK6Z2VlkZeXx8yZMwHYsWMHq1atQqVSYWtrq+TsA7h+/TrPPPMMTz31lFJrt2HDBpKSkigoKGDv3r11jr6ZmppKXFwcHh4eSrB3+PBhYmNj+eOPP1CpVDg7O/P2229jaGhIVlYWH3zwAWVlZejr6/P6669rDAbz6aef8sUXX6Cvr49KpeKRRx4hNDQUfX19nn/+eY4cOcJnn32GjY0NL774IklJSRIACiGEEEKn1FW7qEtBp+japOavldSV2qG5kpOTATh79izp6elaBX+JiYkkJCQAVYOjrF27ls8//xwTExMuXryoMe/777/P3/72N41pDz74IKNGjWLKlCkNbsfb21sJGP/44w9ef/11li9fjpOTE5WVlXzzzTcUFxfz+++/ExsbyyeffMJ9993HmTNneOmll7CwsMDW1pbPP/+cH3/8kc2bN9O7d29KS0tZt24dJSUl6Ovrs379ep5//nkAevTowSOPPMKOHTvw9fXV7iAKIUQb0Xa4cukbKETnJNeyEG1Dp4K/+mRnZxMTE4OpqSn29vacOXOGNWvWsHLlSoyMjJg6dSoAo0ePZvXq1VhYWCh93eLj48nPz8fPz49x48axc+dOIiMjsbOzA6pqCBcuXIiBgQH6+vpKbd3mzZuZNGkSJiYmAErzSYAjR45w8eJF3NzcOHLkiDL9gQceaPK+bdy4kbFjx+Lk5ARUpbHw8vICIDY2lmnTpnHfffcBcN999xEcHMzHH3/M0qVLWb16NRs2bKB3795AVYDXUE3pk08+SXx8fJOCPxlGvelkEAXR0TV0DrfWeavtg588IHYu0oSv7ckLFCG6Np0K/m4f3XPatGl4eHgQGRlJUlISVlZWzJ49u0nrnDt3rsaAMCYmJqSmphIREcGpU6coLS3F1taWlJQU7O3tleVOnz4NVAWHFRUVzJw5k5EjR1JRUUFsbCxxcXHs3bv3jvf55MmTjB07ts7v/vOf/yiBbTVHR0c2bdrE9evXuXHjhhIYamPIkCH8+uuvTSqfNj/G2gQ7XelHvSvtq+ic5BxuGxL43Pl+yzFsOgn2mk5ehIvORKeCv7qafR4/fhwLCwslbYOvr2+T0hvczsvLi4SEBMLCwkhJSVHSOxQVFWn00bt16xa///4769ev5/z580yaNIn09HS2b9/OyJEj6d+/f7PLoK26umNWp54AzWT3P/zwA8uWLePatWssW7aMBx+sfXPX09NDX1+f69evY2xs3GLlrHkT1LbWq63UfMMpP3iiK+rMA4R0dPI3uHNyDFuH1A5q0oXzrL4XHe3RUqMlVJdbl8vYWelU8FefmkFOTXp6elRUVCifS0pKGl2XoaEhrq6u7Nq1i8zMTFJSUoCqwPPatWvKfH379mX48OHo6+tz3333MXDgQE6fPk1ubi4HDhzg888/p7i4mLKyMoyMjAgNDW3Wvg0ePJijR49qDOJS87sjR45ga2urTDt69CiDBg3C2NgYQ0NDzpw5w3333Yebmxtubm5MmzaNsrKyerdXWlqKgYFBs8qqDV27iLv6D5YQ2l6T2uaxvJ1cY0K0vdau8ZTrWvfU93fWteeumhqqMdXlcnd2Oh/8WVtbo1arKSgowNLSkoyMDOW7AQMGsHv3bqAqKFKr1bWW79WrF8XFxRrTAgICCAkJwcXFhT59+ijb2b59uzLPk08+SUZGBv7+/ly6dInTp09z3333aYz4WZ2jr7mBH8DkyZMJCAhg1KhRDBs2DIC0tDRcXV2ZOnUqr7/+Og8//DAWFhao1WrWrFnDP/7xDwCCg4NZuHAhK1asoHfv3lRWVjYYAF++fBkzMzP09fWbXV4hRPNpWxPdHjXW8rAnxJ1rq2tXHpxFRyDnqW7SqeDv9j5/bm5uhIaGEhUVRXBwMKampjg7O3Py5EkAPD09SUtLw8/PD0dHR6VpaE02Njbo6enh6+uLv78/QUFBODg4YGxsrDT5BBgxYgSxsbFKs0o3Nzd++uknvL290dPTIywsDFNT0wbL/9lnn5GYmMgff/yBr68vjz/+eKO5++6++26WL19ObGwsFy9epFu3bowYMYKnn36ae+65h9DQUKZPn66kepg3b54yWM3EiRP53//+R0BAAD169KBXr144OTnVO/BMTk4Ojz/+eIPlEUK0HhnURIjOTa5d0dVJP1zdp1N5/rSRk5OjMYBLcxQWFjJlyhQyMzM1ErtHR0fj7u6Oq6trSxS1TtW1hdWpHlrb888/T1hYGI6OjsycOZM5c+Zgbd32F2NjTcrkB7N1NNQXwPLGFTnuQgjRRLrWH07XytMa2qrvcmsN7KLteAja/i7XXF/NZWRgmtYjef46sG3btrFixQrCw8M1Aj+AkJAQDh061Krb79mzJ9nZ2URERDRaK3innn/+ec6cOYO+vj6lpaU8+eST7RL4Qef8MWpJrXXDlhu/EEK0LF37PdO18rSGtvota63ttPR6O2L/P6E7OlzNnxBCiM6vK9RmCCGE6Bik5q+N2NnZMXToUOWzj49Pg0nMGxIYGEhycjJqtZrc3FzGjBnT6DJZWVnk5eUxc+ZMYmJiyMnJAar6Jl68eJH9+/dz/PhxFi5cyPXr1+nWrRvTp0/H29sbgL179xIXF0dZWRn29vYsWrSI7t01D3lqaipxcXF4eHgoNYGHDx8mNjaWP/74A5VKhbOzMw888ICS4iI/P5+BAwfSrVs33NzcsLa2rrMp6fPPP8+RI0f47LPPsLGx4cUXXyQpKalWGYQQQtdIsCeE7pB+XEJ0HjodBdSV96+5kpOTATh79izp6elaBX+JiYkkJCQA8NZbbynT169fz7Fjx5QyxsbGcv/991NYWMj48eN57LHHMDY2Jjw8nHXr1jFw4EA++OADtm7dSkBAQK3teHt7K4HbH3/8weuvv87y5ctxcnKisrKSb775BhcXFyZNmgSAu7s7SUlJSl7C1NTUOsu/fv16nn/+eQB69OjBI488wo4dO/D19dXqmAkhhBCiY2rJkUc7W8DX1NQ28jJKdCY6HfzVJzs7m5iYGExNTbG3t+fMmTOsWbOGlStXYmRkxNSpUwEYPXo0q1evxsLCAicnJ3Jzc4mPjyc/Px8/Pz/GjRvHzp07iYyMVEbQDAwMZOHChRgYGKCvr6+R+L1aRkYGs2bNAmDgwIHK9L59+2JmZsalS5coLy+nR48eyvePPvooa9asqTP4q2njxo2MHTsWJycnoCrHoZeX150fNKrSV8THx0vw1wIaapImieWFEEK0N/n9qZ8cG9GV6XTwd3vqh2nTpuHh4UFkZCRJSUlYWVkxe/bsJq1z7ty5GqOFmpiYkJqaSkREBKdOnaK0tBRbW1tSUlKwt7evtfzZs2dRq9U8/PDDtb47fPgwZWVlWFpaolKpKC8v59dff8XR0ZGvv/6a8+fPN1q+kydPMnbs2Cbtk7aGDBnCr7/+2irrro+2I1xV6yhvFxv64ZAfFVFTfW+YO+p5Ii83dFNnGOWvrUZ01AUd+TrqbPc0ceekWXDHotPBX13NPo8fP46FhYWS08/X11fpC9ccXl5eJCQkEBYWRkpKipL7r6ioqN5aP09PT/T09DSmX7hwgXnz5hEbG6uMIrp8+XIWL15MaWkpjz76aK1l2pqenh76+vpcv34dY2PjNtmm3AREV9fZHohq7k9DP/i69iDfkR+2tdEZ7rWdYR+01ZLnYFs/eHfG66ezas650Zx7ZVe6djsDnQ7+6qNSqeqcrqenR0VFhfK5pKSk0XUZGhri6urKrl27yMzMJCUlBagKPK9du1Zr/h07dtQaWOX69etMmzaN2bNnM3z4cGW6k5MTmzZtAuDHH3/k9OnTjZZn8ODBHD16lCeffLLReZujtLQUAwODVlm3EKJraegHX9ceBuSBVXRWunatica1VU19c9Yr98rOr8MFf9bW1qjVagoKCrC0tCQjI0P5bsCAAezevRuAo0ePolaray3fq1cviouLNaYFBAQQEhKCi4sLffr0Ubazfft2jfl+++03rl69qvTHg6pg6tVXX8XPz49nnnlGY/6LFy9ibm5OaWkpH330ESEhIY3u3+TJkwkICGDUqFEMGzYMgLS0NFxdXbnnnnsaXb4hly9fxszMDH19/TtajxBCCHG7hgbR6OgPlNLUUbQkCdhFe9Lp4O/2Pn9ubm6EhoYSFRVFcHAwpqamODs7c/LkSQA8PT1JS0vDz88PR0dHpWloTTY2Nujp6eHr64u/vz9BQUE4ODhgbGysNPkEGDFiBLGxsVRWVio1jRkZGXh7e2vUPGZmZrJ//36uXLnC1q1bAViyZAl2dnYkJiaye/duKioqmDBhAo888kij+3z33XezfPlyYmNjuXjxIt26dWPEiBE8/fTTDS63detWsrKylM+bN2+mX79+GvPk5OTw+OOPN1oGIYQQoqk6SiDUnKZw7bVv1WWVYKF1NDQugRzz2rQZx0GOm+7r8Enec3JyNAZwaY7CwkKmTJlCZmam0l8PIDo6Gnd3d1xdXVuiqHVKTU2tM0dfS3n++ecJCwvD0dGRmTNnMmfOHKyt5cIUoj6SXFwIIYQQNUmS905k27ZtrFixgvDwcI3ADyAkJIRDhw616vZ79uxJdnY2ERERSpL3lvL8889z5swZ9PX1KS0t5cknn5TAT4hGdNRgr7MPaHKntB15WN5ai9bQ2Pkn550Qoq3oTM2fnZ0dQ4cOVT77+PgQHBzcrHUFBgaSnJyMWq0mNzdXq4TuWVlZ5OXlMXPmTGJiYsjJyQGqmp5evHiR/fv3A7B06VL27NkDwIwZM/D29gZg7969xMXFUVFRgZGREUuWLMHKykpjG6mpqcTFxeHh4cGiRYvIyclhxowZ3Hfffdy8eZO7776bl19+mSeeeAKAlStXsnnzZszMzLh58yZDhw5l9uzZDB48GKgK7i5cuECPHj0oKyvD1dWV2bNn07t3b/73v//x3HPPkZ+fT3Z2NgDz5s3j448/btYxFUII0XYkmBdCCN0hNX+toK60Ds2VnJwMVOXkS09P1yr4S0xMJCEhAYC33npLmb5+/XqOHTsGwO7duzl27Bjbtm2jtLSUyZMnM3LkSIyNjVm4cCEJCQkMGjSIjRs38uGHH7JkyZJa2/H29tZo4uni4qI0WT1+/DivvvoqPXv2VPoHBgUFKUnrd+zYwQsvvMBXX32lpKFYtmwZjo6OlJaWsnz5cmbMmMGGDRuU4+nu7g6AmZkZ9957LwcOHMDZ2blpB1QHteaDka4NUS+E0F3V96KWvg8VGPUBdD+FRkckgbUQoivTmeCvPtnZ2cTExGBqaoq9vT1nzpxhzZo1rFy5EiMjIyUwGj16NKtXr8bCwgInJydyc3OJj48nPz8fPz8/xo0bx86dO4mMjMTOzg6oqiFcuHAhBgYG6Ovr15vXb9asWQD85z//YcSIEXTv3p3u3btja2tLdna2Uvt3/fp15b/33ntvk/fVzs5OCd7qGhzG29ub3bt389VXX/HCCy9ofNejRw/mzZvHU089RV5eHra2trWW9/Dw4KuvvuoUwV9r/mDLQ5QQQlutdS+q7z4k96c7JwFf02nbbLo+ct4KoTt0Jvi7fWTPadOm4eHhQWRkJElJSVhZWTF79uwmrXPu3Lkag8GYmJiQmppKREQEp06dorS0FFtbW1JSUrC3t6+1/NmzZ1Gr1Tz88MMA2NrasmrVKl588UVu3rxJTk6O0gRz0aJFBAcHY2BggLGxcbMTz9vb2zfYNPOBBx7gt9/qvgnr6elha2vLb7/9Vmfw5+joyAcffNCsct2phnLayOhRoiNqqzxNQgjR3uT+JkTnoTPBX13NPo8fP46FhYWSssHX17fZQRWAl5cXCQkJhIWFkZKSoqR2KCoqqrfWz9PTEz09PQAee+wxfv31VwIDAzEzM2P48OHKd+vWrWPt2rUMGzaMxMREFi9e3KwBXO60C2ZDy5uZmXHhwoU7Wn9zdaRk0PXR9s2n5Y0r8ma5C+go560QQgghRDWdCf7qUzOnXk16enpUVFQon0tKShpdl6GhIa6uruzatYvMzExSUlKAqsDz2rVrtebfsWNHrRQM06dPZ/r06UBVzeL999/PpUuXyMvLU5Kye3t78/LLL2u3g7c5duwYgwYNavB7BweHOr+7desW//73v+sd0bOkpAQDA4Nmlau96cLw+/KwL4RoSZJjTAghRFvT6eDP2toatVpNQUEBlpaWZGRkKN8NGDCA3bt3A3D06FHUanWt5Xv16kVxcbHGtICAAEJCQnBxcaFPnz7KdrZv364x32+//cbVq1dxcnJSpt26dYurV69iampKXl4eJ06c4NFHHwXg2rVrnDp1ioEDB/LTTz81GMDVJy8vj4SEhHprDL/55ht++uknwsPDa31XVlbGihUr6N+/f51NPgFOnz7NkCFDmlwuXdCWwV5z+jbIg5oQoqnkviGEEKKt6Uzwd3ufPzc3N0JDQ4mKiiI4OBhTU1OcnZ05efIkAJ6enqSlpeHn54ejo6PSNLQmGxsb9PT08PX1xd/fn6CgIBwcHDA2NlaafAKMGDGC2NhYKisrlZrGjIwMvL29NWoey8vLmTRpEgDGxsYsXbqU7t2rDmF0dDSvvfYaKpUKExMTYmJitNrv/fv3M3bsWG7evIm5uTlvv/22xmAv69atY/v27dy8eZMhQ4aQlJSk0UQ1NDSUHj16UFpaiqurqzJiaV1ycnIYNWpUw+XRsm9eWz203F7jV00GfBFCdEQyWqcQQghtzZ8/n927d2Nubk56enqt7ysrK1m0aBF79uyhZ8+eLFmypM5xTGrSmTx/2sjJydEYwKU5CgsLmTJlCpmZmRpJ3aOjo3F3d8fV1bUlilqn1NRUjhw5UqspaWtyd3dny5YtmJmZMWnSJBISEjAxMWmz7QuhrabWuOryw3J7vLQQQgghROtorzx/+/btw8jIiDfffLPO4G/Pnj2sX7+ejz76iEOHDrFo0SK+/PLLBtepMzV/bWHbtm2sWLGC8PBwjcAPICQkhEOHDrXq9nv27El2djYRERHNGgymKaqTvJeVldGtWzcuXbrEiy++KIGf0Fm6HMw1VUcP8uoLXm/X0fdTCCGE0GUjRoyos2tbtV27djF27FhUKhXDhw/n6tWrXLhwocGUcx2q5k8IcWcaeqiXB/mOQfqkCtHxtUc3iqbQhUHWOjo5hg2rvgZ08fyvS2vV/M2wseaLL75QPj/33HM899xzGvOo1WpCQkLqrPmbNm0ar7zyCi4uLgC88MILhIaG4ujoWO82O0TNn52dHUOHDlU++/j4EBwc3Kx1BQYGkpycjFqtJjc3lzFjxjS6TFZWFnl5ecycOZNz587x5ptvcu3aNW7dukVoaCiPP/64Mu/169d55plneOqpp5TmnRMnTlQGnrl48SJ//etfa/XNS01NJS4uDg8PDxYtWkROTg4zZszgvvvu4+bNm9x99928/PLLPPHEE8oyX3zxBZ9++ilQ1QcxPDxc+ePPnTuXH374gaioKLy8vAgKCuKDDz6Qmr8uTn58Or6O8kPZVJI3UXQlun5+Fxj10fhcfx2CqI/83jZM16+BtlJXsNcUddXh1ZcpoVqHCP7qygHYXMnJyUBVAvf09HStgr/ExEQlWPvwww955plnmDhxIv/5z38IDg7mu+++U+Z9//33+dvf/qax/KZNm5T/nzVrFh4eHnVux9vbW6M/oIuLi9K/8fjx47z66qv07NmTRx55hO+//54vvviCTZs2YWZmxtGjR3n11Vf58ssvueeee4iPj9cYFdTPz49NmzYpaSraW803YnKDFELowoOA3JdEta6ehqMr7GNHo02rD/m7dT39+vXj/Pnzyufz58832OQTOkjwV5/s7GxiYmIwNTXF3t6eM2fOsGbNGlauXImRkRFTp04FYPTo0axevRoLCwucnJzIzc0lPj6e/Px8/Pz8GDduHDt37iQyMhI7OzugqoZw4cKFGBgYoK+vr4ywqVKpuH79OlCV3qHmAT5y5AgXL17Ezc2NI0eO1Crv9evX+fnnn1m8uOlVx3Z2dsyYMYMNGzbwyCOP8NFHHzFv3jylXPb29owdO5aNGzcye/bsWsu7u7szadIknQn+5MGq6+rqD1Wi9TSnKZ3G+VijtqOgkQetlj5X62siJk3H2ofci4SukXNS1MXd3Z0NGzbg4+PDoUOHuOuuuzpH8Hd7Gohp06bh4eFBZGQkSUlJWFlZ1RnwNGTu3LkaI4eamJiQmppKREQEp06dorS0FFtbW1JSUjSGTJ05cyZTp05lw4YN3Lx5U2l2WVFRQWxsLHFxcezdu7fObWZlZfHII49gbGzcxCNQxd7eno8//hiA//znP7WSvTs4OLBt27Y6lzUxMaG0tJTLly9jamrarO03hzYPYw0199LmTby8re9Y5AescfLA3zzNObd05Xys728sf3shxO10vc9ofeS3renmzJnDL7/8wuXLlxk5ciSzZs2ivLwcgAkTJvD444+zZ88ennrqKQwNDbVKNdchgr+6mn0eP34cCwsLJb+fr68vmzdvbvY2vLy8SEhIICwsjJSUFCUPYFFRkUZevYyMDMaNG8dLL71Ebm4uYWFhpKens2nTJkaOHEn//v3r3UZ6ejoBAQHNLqM2Y/M01M7XzMyMCxcutGnwp81NqaF5tLkxyM1DdDZyTgshOhpdeBGrS32HWzPQ6UgBX03y29Z0y5cvb/B7lUrFO++806R1dojgrz71BTp6enpUVFQon0tKShpdl6GhIa6uruzatYvMzExSUlKAqsDz2rVrynxbtmwhMTERACcnJ0pKSrh8+TK5ubkcOHCAzz//nOLiYsrKyjAyMiI0NBSAy5cv8+uvv/LPf/6z2ft77NgxBg0aBMCgQYM4cuSIRkL4o0ePKt/XpbS0lJ49ezZ7+6Jrkjd1oj3owoOkEB2NNmlaWut60oXrtK2Dogb74dVoRt5RgzXROXXY4M/a2hq1Wk1BQQGWlpZkZGQo3w0YMIDdu3cDVQFRXfkxevXqpYzAWS0gIICQkBBcXFzo06ePsp3t27cr8/Tv35+9e/fi7+9Pfn4+JSUlmJmZER8fr8xTncy9OvAD+Prrrxk1ahQGBgbN2t+8vDwSEhKU/IAvv/wyy5YtIzExEVNTU44fP87WrVvrrf2srKykqKiIAQMGNGv7HUVLBCr13cy76s1bF37QRdfTUc676ntOW5VX7k+iIR3luuks5LoTHVGHCP5u7/Pn5uZGaGgoUVFRBAcHY2pqirOzMydPngTA09OTtLQ0/Pz8cHR0VJqG1mRjY4Oenh6+vr74+/sTFBSEg4MDxsbGSpNPqEquGBsbS2VlJSqVivDwcN5++23WrVuHSqViyZIljQ6pCrBjxw5eeeWVJu33/v37GTt2LDdv3sTc3Jy3335bqenz8PCgsLCQwMBAVCoVvXr1YunSpfV28jxy5AjDhw+ne/e2/ZO3VB4XbfPTtcQPn9zMRXuTWq+Oo63/PnJ/EkIIcSc6TZL3nJwcjQFcmqOwsJApU6aQmZlJt27dlOnR0dG4u7vj6uraEkWtU3VtYc1UD3cqPDycUaNG4eXlRXR0NB4eHhrNREXr0zYhtzzQaUeaoAqhnfpemMk1I4Ru0fY5oSZ5Zmh7rZXkfc+C+a2y3oZ0iJq/trBt2zZWrFhBeHi4RuAHEBISwqFDh1p1+z179iQ7O5uIiAilaeedmDt3Lrm5uXh6egIwdOhQCfzagdygW5Y8uAqhHblWRFegTR/H+ujKNSLPCaKt6WzNn52dHUOHDlU++/j4EBwc3Kx1BQYGkpycjFqtJjc3V6vE7llZWeTl5TFz5kzOnj3LW2+9xaVLl+jTpw9Lly6lX79+HD9+nIULF3L9+nW6devG9OnT8fb2BuDMmTPMmTOHP//8kwceeIC4uDh69OihsY3U1FTi4uLw8PBg0aJF5OTkMGPGDCwsLJR53nzzTVxdXWsdj3/+858cO3aMjRs3kpSUBFQ1E33vvfdISUlh586drFixAmtra9asWcOGDRswNDRk/PjxzTqGQgghhGiY5DEVonOSmr82UFd6h+ZKTk4G4OzZs6Snp2sV/CUmJpKQkABAbGwsY8eOZdy4cezdu5f4+HiWLl1Kz549iY2N5f7776ewsJDx48fz2GOP0bt3b5YtW0ZQUBA+Pj4sWLCALVu2MHHixFrb8fb21mjq6eLiUmfT1bqOh4WFBVu2bOGrr77imWee4d133+Xdd9+le/fueHt7Y25uzieffALA+PHjmTBhQqsHf5KoWHQUutyvTpfLJoSonwR4HYM0ixZdmc4Gf/XJzs4mJiYGU1NT7O3tOXPmDGvWrGHlypUYGRkxdepUAEaPHs3q1auxsLDAycmJ3Nxc4uPjyc/Px8/Pj3HjxrFz504iIyOxs7MDqmoIFy5ciIGBAfr6+kp+v/z8fN566y0AHn74YV599VUABg4cqJSrb9++mJmZcenSJe666y5+/vlnZQTQcePGsWrVqjqDvzsVGRlJUFAQ//nPf3B0dOTBB+u+cRkaGjJgwAAOHz7MX//61xYvR7XmJCqWN6WiPejyj7wul00IXaJtsz+5pkRNbX0+aDtonRBtQWeDv9tH+Jw2bRoeHh5ERkaSlJSElZUVs2fPbtI6586dqzEojImJCampqURERHDq1ClKS0uxtbUlJSUFe3t7ZTlbW1u++eYbXnjhBb799luKi4u5fPmyRrL0w4cPU1ZWhqWlJZcvX6Z3797KyJr9+vWjsLBQqzLu379fY79XrlyJpaWlxvGwsLBQ8gXed999eHt7s2HDBr799tsG1+3g4MD+/ftbNfhrDgnwhBBCNIc8OIuOoLOcp7e/rJfnt45JZ4O/upo5Hj9+HAsLCyV1g6+vb7157bTh5eVFQkICYWFhpKSkKCkeioqKlFo/gLCwMN577z22bt2Ki4sLffv21UiZcOHCBebNm0dsbGytwWKqaZMOAprW7BOgoqKCf/3rXxgZGXHu3DmNct/O3Nyc335r+qhSbam9modqM9qW3OSEEG2lpdLkdCQ178MdZb+lS4PoSjrKdSkaprPBX33qC6L09PSoqKhQPpeUlDS6LkNDQ1xdXdm1axeZmZmkpKQAVYHWtWvXlPn69u3LqlWrACguLmbnzp3cddddAFy/fp1p06Yxe/Zshg8fDoCpqSlXr16lvLyc7t27c/78+Xrz792pjRs3MnToUF5//XWioqL44osv6j1GJSUlzU4y31ba64dTbmhC1E2aK7WPlrwndZSgSpfLVp+GrgHpuyuE0EUdKviztrZGrVZTUFCApaUlGRkZyncDBgxg9+7dABw9ehS1Wl1r+V69elFcXKwxLSAggJCQEFxcXOjTp4+yne3btyvzVI/y2a1bN9auXasMmlJaWsqrr76Kn58fzzzzjDK/SqXioYce4ptvvsHHx4etW7fi7u7eUodBUVRUxKeffsqWLVswMzPjyy+/5Msvv+TZZ5+tc/7Tp0/X2ydQCCHqIg+tHV9bBVWtFex0lOD1dnLtCCF0kc4Gf7f3+XNzcyM0NJSoqCiCg4MxNTXF2dmZkydPAuDp6UlaWhp+fn44OjoqTUNrsrGxQU9PD19fX/z9/QkKCsLBwQFjY2OlySfAiBEjiI2NpbKyEpVKxS+//MLy5ctRqVS4uLjwzjvvAJCZmcn+/fu5cuUKW7duBWDJkiXY2dkxb9483njjDd5//33s7OwICAjQar9v7/M3ffp0vLy86px3yZIlvPzyy0pTz7feeotJkybx9NNPK4FsTQcPHlQGqxFCCCFaUmsFOx0p4BNCVzU3J6K8xOh8dDbPnzZycnI0BnBpjsLCQqZMmUJmZqZGf73o6Gjc3d1xdXVtiaLWKTU1lSNHjmikemhJNY/PsWPH+PTTT1m6dGmrbEsIIYQQQlTpjCOZ17dPHXV/mkLy/HUS27ZtY8WKFYSHh9caqCUkJIRDhw616vZ79uxJdnY2ERERLFq0qEXXvWPHDlatWqWMWnr58mVef/31Ft2GEKJz6qjN7NqKDBAlOgtJldF6OuM9oDPuk7aedrRvfKYOokPX/AkhhBCiNl0dbESbwBm69kOmEEL3LNq6vfGZmiFinG+rrLch7VrzZ2dnx9ChQ5XPPj4+BAcHN2tdgYGBJCcno1aryc3NZcyYMY0uk5WVRV5eHjNnzmTfvn3ExMRw4sQJli9frtHPbuvWrXz44YdAVR+8cePGAXDmzBnmzJnDn3/+yQMPPEBcXBw9evRg+/btfPTRR0DVIDMLFy7E1ta23v1fu3Ytffv2xd3dnV69eim1kCNGjODWrVscPHiQsrIy1Gq1klh++vTp7N69m19++YW77rqLyspK5s+fzyOPPAJU5TT84YcfiIqKwsvLi6CgID744ANMTEyadXyFEEJ0HLoU8NUkQV3H1FVaA0geO9EVtGvwV1/uuuZITk4G4OzZs6Snp2sV/CUmJpKQkABA//79Wbx4MZ988onGPFeuXGHVqlWkpKSgUqnw9/fH3d0dExMTli1bRlBQED4+PixYsIAtW7YwceJELCws2LBhAyYmJuzZs4fIyEi+/PLLWtuva/+TkpLqzNWnVqsJCQnRmH/37t2EhYXh5eXFzz//zIIFC9i5cycA8fHxhIeHK/P6+fmxadMmpk+f3uhxEUIIXdIeD54drb9Oa5ZXV2sRRdvRxXO+NXSV/RRdm072+cvOziYmJgZTU1Ps7e05c+YMa9asYeXKlRgZGTF16lQARo8ezerVq7GwsMDJyYnc3Fzi4+PJz8/Hz8+PcePGsXPnTiIjI7GzswOqaggXLlyIgYEB+vr6SqBlYWEBUKvv348//sijjz6qjJ756KOP8sMPP+Dj48PPP/9MfHw8AOPGjWPVqlVMnDhRI53C8OHDOX/+fKseLwAnJycKCwvr/d7d3Z1JkyZJ8CeEuCPt0WyvPR7IOtpDYGuWVwI+IYToPNo1+Ls9ncO0adPw8PAgMjKSpKQkrKysmD17dpPWOXfuXI0RQE1MTEhNTSUiIoJTp05RWlqKra0tKSkpymAoDSksLKRfv37K5759+1JYWMjly5fp3bs33btXHcJ+/frVGXxt2bKFkSNHal3+F154QQlAx40bR1BQkFbL/fDDDzz55JP1fm9iYkJpaSmXL1/G1NRU6/IIIURNHS0oEkII0T60GVBIXi61PZ1r9nn8+HEsLCyUPH2+vr5s3ry52dvw8vIiISGBsLAwUlJSlHx+RUVFdTavvF1d4+GoVKo65719+s8//8yWLVvYtGmT1uWtr9lnfeLi4li6dCmXLl3iiy++aHBeMzMzLly40KWCP21rKW4nD7iiI5N+K0KIjqyhoEGChdbVnOem+n5j5G+lm3Sy2Wd9wZWenh4VFRXK55KSkkbXZWhoiKurK7t27SIzM5OUlBSgKvC8du1ao8v369ePX375RflcWFjI3/72N0xNTbl69Srl5eV0796d8+fPc++99yrz5eXl8fbbb/PRRx+1arAVFhbG008/zWeffUZ4eDipqan1zltaWkrPnj1brSy6qKM89LbkzVZXSD+h9qPr54YQQjfo6kAu8pvRtmr+XlvWmC5/h85J54I/a2tr1Go1BQUFWFpakpGRoXw3YMAAdu/eDcDRo0dRq9W1lu/VqxfFxcUa0wICAggJCcHFxUXpu2dtbc327Y0P2/rYY4+xfPly/vzzT6CqD+CcOXNQqVQ89NBDfPPNN/j4+LB161bc3d0BOHfuHLNmzSIuLk4ZnbM1devWjRdeeIFt27bxww8/4ObmVmueyspKioqKGDBgQJPWLQ/wbUOXfnRbipwvoqVo+4Cqqw+yQugquU4EyO91V6NTff7c3NwIDQ0lKiqK4OBgTE1NcXZ25uTJkwB4enqSlpaGn58fjo6OStPQmmxsbNDT08PX1xd/f3+CgoJwcHDA2NhYafIJVWkUYmNjqaysRKVScfjwYWbOnMnVq1f5/vvvWblyJRkZGfTp04cZM2bw97//HYBXX31VCSDnzZvHG2+8wfvvv4+dnR0BAQEA/POf/+TKlSu8++67QFWNZUM1cjXV7PNnY2NDXFycVsupVCqmT59OYmJincHfkSNHGD58uNJHUVtyQ2h7knRXCE3aPqDKg2znd/v9Ue6DQrQPednWcel8kvecnByNAVyao7CwkClTppCZmakxmmd0dDTu7u64urq2RFGbrHqE0tYSHh7OqFGj8PLyIjo6Gg8PDyUPoBCi6aQmXAghhOh6JMl7B7Jt2zZWrFhBeHh4rTQOISEhHDp0qJ1KVtVE1c/PT0ny3pLmzp1Lbm4unp6eAAwdOlSrwK89hnEXoqNoKODTpbegrTlYgrY10y25TSGEEEK0jHap+bOzs2Po0KHKZx8fH4KDg5u1rsDAQJKTk1Gr1eTm5mqV3D0rK4u8vDxmzpzJvn37iImJ4cSJEyxfvhwvLy9lvq1bt/Lhhx8CMH36dMaNGwfA3r17iYuLo6KiAiMjI5YsWYKVlRXXrl1j3rx5nDt3jlu3bvHSSy8xfvz4eve/Ouhzd3enV69eSnD6zjvvcO+99xISEsKbb77JsmXLACgoKODee++lZ8+e2NjYMH78eGbMmIGFhQUVFRWYm5sTHx+Pubk5O3bsYMWKFVhbW7NmzRo2bNiAoaFhneXpiNrqAbTmA73ljSvyENsC6nvB0N4B052q75yUc0bcCXkhJ0Tn01GeLZrTzFqXXoS2pM5U89cuwV9rNHdsSvPQwMBAEhISMDMzQ61Wc/36dT755BPc3d2V4O/KlSuMHz+elJQUVCoV/v7+pKamYmJigqenJwkJCQwaNIiNGzfy66+/smTJElavXq0EgJcuXcLLy4sff/yRHj16NLj/7u7ubNmyRSPFg1qtJiQkhPT0dGXa888/T1hYGI6OjnXuc3x8PPr6+rz22mu1vr958yYTJkxg27ZtzTvAokOSgEQIIYQQ4s50puBPp5p9ZmdnExMTg6mpKfb29pw5c4Y1a9awcuVKjIyMmDp1KgCjR49m9erVWFhYKIFUfHw8+fn5+Pn5MW7cOHbu3ElkZCR2dnZAVcC3cOFCDAwM0NfXVwItCwsLgFpNQn/88UceffRRZXCXRx99lB9++IHRo0cDcP36deW/1SkeVCoVxcXFVFZWUlxcjImJSZMHWGmu6m1aWlrW+b2hoSEDBgzg8OHD/PWvf22TMon2J0GeEEIbDdUwdqa39x2V5O5sOskVKETd2iX4u32Uz2nTpuHh4UFkZCRJSUlYWVkxe/bsJq1z7ty5GrVgJiYmpKamEhERwalTpygtLcXW1paUlBTs7e0bXV9hYSH9+vVTPvft25fCwkIAFi1aRHBwMAYGBhgbGytJ6CdNmsT06dNxc3OjuLiYFStW1Aoq61M9ymePHj348ssvtd7v/fv34+fnx5UrVzA0NGTOnDn1zuvg4MD+/fsl+BOinUgTPqGrTaJ0qSyitrb4+3S2FwAS4AlRt3YJ/nr27ElaWprGtOPHj2NhYaGkb/D19VWCqubw8vIiISGBsLAwUlJSlDQPRUVFGs0r61NXa9jq5PPr1q1j7dq1DBs2jMTERBYvXsyiRYv48ccfsbOz47PPPqOgoIAXX3wRFxcXjI2NG91eUlKSVuW6nYuLixLwrl27lri4OKKiouqc19zcnN9+a3oycdE0uvpw1xk0dGyrv2uvY67N313OByHngNBVcm4K0TXoVLPP6uDqdnp6elRUVCifS0pKGl2XoaEhrq6u7Nq1i8zMTFJSUoCqwPPatWuNLt+vXz9++eUX5XNhYSF/+9vfuHTpEnl5eQwbNgwAb29vXn75ZQBSU1MJDg5GpVJhZWWFhYUFv/32W5vVtHl4eDBr1qx6vy8pKcHAwKBNytKVyQ9o62no2Lb3cW/v7QshhOhcJK+laA06E/xZW1ujVqspKCjA0tKSjIwM5bsBAwawe/duAI4ePYpara61fK9evSguLtaYFhAQQEhICC4uLkrfPWtra7Zvb7zT5mOPPcby5cv5888/gao+gHPmzMHY2Jhr165x6tQpBg4cyE8//cSgQYMA6N+/P3v37sXFxYU//viDU6dOKX0K28KBAwfq7fMHcPr0aR58UG4cQgjtm6DeToJcIYRoGxLsidagE33+3NzcCA0NJSoqiuDgYExNTXF2dubkyZMAeHp6kpaWhp+fH46OjkrT0JpsbGzQ09PD19cXf39/goKCcHBwwNjYWGnyCTBixAhiY2OprKxEpVJx+PBhZs6cydWrV/n+++9ZuXIlGRkZ9OnThxkzZvD3v/8dgFdffVUJIKOjo3nttddQqVSYmJgQExMDwIwZM5g/fz5jxoyhsrKS0NDQZjXlbIrqPn+VlZXcddddREdH1zvvwYMHefXVV1u1PEKIjkGCuNpqvmXXlYcubQf60LUBQXStPB2FvJQRQrS2dkn1oI2mpG6oT2FhIVOmTCEzM1Nj4JXo6Gjc3d1xdXVtiaI2WWukuqhLzWN47NgxPv30U5YuXdrq2xWiPXW2QQuEEC1L7hFC1E9GSa2bpHroALZt28aKFSsIDw+vNeJmSEgIhw4daqeSVTVR9fPzU5K8t4YdO3awatUqZWTTy5cv8/rrr7fKtkTLquvG25VvuE0lD29tp66HaDn+QtfJOSpE/eR5o/PTieDPzs6OoUOHKp99fHwIDg7moYceavK6AgMDSU5OxsXFhdDQUJ555pla89x99914eHgon7OyssjLy2PmzJns27ePmJgYTpw4wfLly5Wk7wBTp07l0KFDODs7a9RI7t27l7i4OCoqKjAyMmLJkiVYWVkpCd/PnTvHrVu3eOmllxg/fjw//vhjnftfHQwWFxcTFxfHTz/9hLGxMd26dSMwMJBnn30WgFOnThETE8Pp06fp3r07Q4cOJTIykvz8fI3a0rKyMq5evaosc/78+Tbtg6gLOmKSc10umxA1yUN029PFpqlCtLaaL5osb1yRc18H1FeDLr8Luk8ngr+6Uj80V3JyMgBnz54lPT2dMWPGNLpMYmIiCQkJQNWgLYsXL+aTTz6pNd/LL7/MzZs3+eKLLzSmL1y4kISEBAYNGsTGjRv58MMPWbJkCRs3bmTQoEGsXr2aS5cu4eXlxZgxY+jRo4fG8rfv/9tvv819993Hzp076datG5cuXWLLli1A1Yid06ZNIzw8HHd3dwB+/vlnLl26pLFOb29vzM3Nlf0YP348EyZMYPz48Y0ej85EfiCEEJ2J3NM6pqb05ZOH59rkmOge+Zt0XDoR/NUnOzubmJgYTE1Nsbe358yZM6xZs4aVK1diZGTE1KlTARg9ejSrV6/GwsJC6U8XHx9Pfn4+fn5+jBs3jp07dxIZGYmdnR1QVUO4cOFCDAwM0NfXVwZmqa4Zqys5+yOPPEJOTk6dZb1+/bry33vvvReoSl1RXFxMZWUlxcXFmJiY0L17w4e8oKCAw4cPEx8fr5TBzMyM4OBgAL766iuGDx+uBH4ADz/8MEC9ZYOq1BcDBgzg8OHDkuRdCCGEaEPyoCw6Ihm4qXPSieDv9tE/p02bhoeHB5GRkSQlJWFlZcXs2bObtM65c+dqNIE0MTEhNTWViIgITp06RWlpKba2tqSkpCj94ppr0aJFBAcHY2BggLGxsZKcftKkSUyfPh03NzeKi4tZsWJFnUFlTSdPnsTW1rbe+U6ePNns8jo4OLB//34J/oQQQogmkHxroiuSYK9z0ongr65mn8ePH8fCwkJJ6+Dr66sEVc3h5eVFQkICYWFhpKSkKOkfioqK7jgdw7p161i7di3Dhg0jMTGRxYsXs2jRIn788Ufs7Oz47LPPKCgo4MUXX8TFxQVjY2Ot1/3hhx/y9ddfc/HixVp9BZvK3Nyc335r3jDSDan5Zqij3iikH43oauSNrhDak9+F1tEZnh+E6Gh0Ivirj0qlqnO6np4eFRUVyueSkpJG12VoaIirqyu7du0iMzOTlJQUoCrwvHbtWrPLeOnSJfLy8hg2bBhQ1dfu5ZdfBiA1NZXg4GBUKhVWVlZYWFjw22+/NVjzNnjwYPLy8qioqKBbt25Mnz6d6dOn4+TkpHy/b9++ZpW1pKQEAwODZi3bkM5ww5YfdtHVdIbrVrS9hoaBr4/cX0V95D4kRNvT2eDP2toatVpNQUEBlpaWZGRkKN8NGDCA3bt3A3D06FHUanWt5Xv16kVxcbHGtICAAEJCQnBxcVEStltbW7N9e/Nzd/Tu3Ztr165x6tQpBg4cyE8//cSgQYOAqsFj9u7di4uLC3/88QenTp1qdLRNKysrHBwceP/993n99dfR09OjpKSE6nSMY8aMYe3atezevZtRo0YBVX0jtUkZcfr0aR58sGk/wlI7IIQQopoEckII0bHpRPB3e58/Nzc3QkNDiYqKIjg4GFNTU5ydnTl58iQAnp6epKWl4efnh6Ojo9I0tCYbGxv09PTw9fXF39+foKAgHBwcMDY2Vpp8AowYMYLY2FgqKytRqVQcPnyYmTNncvXqVb7//ntWrlypBJ4TJ07kt99+48aNG4wcOZJFixbh5uZGdHQ0r732GiqVChMTE2JiYgCYMWMG8+fPZ8yYMVRWVhIaGqpVE9NFixYRFxfHU089RZ8+fTAwMCA0NBSoqqlcvXo1MTExxMTE0L17d2xsbIiIiODKlSsNrvfgwYO8+uqrjW6/pjsN9pr6lljXHiykSYrobKrPaTmfhRCiedo7jVRTRo+tJvd8UU1VWV2lpONycnI0BnBpjsLCQqZMmUJmZqbGgCrR0dG4u7vj6uraEkVtsuoRSltazWN27NgxPv30U5YuXdri2xFCCCHagrRGEUK0h0Vbm99KsCER43xbZb0N0Ymav7awbds2VqxYQXh4eK2RNENCQjh06FA7layqiaqfn5+S5L0l7Nixg1WrVikjg16+fJnXX3+9yevpaEk8ZUS2jqUla1alRkuIzq+rXt/a1vR01eMjhNBeh6n5E0KIltRRm/Q29BDYEfZDXtAIITWYQnQ0UvOnBTs7O4YOHap89vHxURKVN1VgYCDJycmo1Wpyc3MZM2ZMo8tkZWWRl5fHzJkz2bdvHzExMZw4cYLly5fj5eUFVKWTWLhwIdevX1dG1vT29gYgPDycX375hbvuuguAJUuWYGdnx/bt2/noo4+Aqhq7hQsXYmtrW+/+V9fmFRcXExcXx08//YSxsTHdunUjMDCQZ599FrVajbe3NwMHDqSsrAwXFxcWLlxIt27dOHnyJO+99x6FhYVUVlbi5+fHjBkzUKlUpKamEhcXR9++fSkpKSEwMJCgoCCgKv3EunXrcHd3Z8GCBcTGxjJy5EgeeeSRZv0NhOhsOurDVkctd7WuHuy1d18hoRs6+nUshOi4Wi34qyt3X3MlJycDcPbsWdLT07UK/hITE0lISACqRt1cvHgxn3zySa0yxsbGcv/991NYWMj48eN57LHH6N27NwBhYWFKoFjNwsKCDRs2YGJiwp49e4iMjOTLL7+stf3b9//tt9/mvvvuY+fOnXTr1o1Lly6xZcsW5XtLS0vS0tIoLy/nhRdeICsri5EjRzJ9+nQWLlzIY489xs2bN5k1axabNm1i0qRJQFVqiQULFnD58mW8vLzw9PSkf//+BAUF0bt3b44cOQLA5MmTiYyMlOBPtCjJjyhE08h1cmeak2oC5LgLIUS1Nu/zl52dTUxMDKamptjb23PmzBnWrFnDypUrMTIyYurUqQCMHj2a1atXY2FhoQyIEh8fT35+Pn5+fowbN46dO3cSGRmJnZ0dUFVDuHDhQgwMDNDX11dG1qxOr3B7X7+BAwcq/9+3b1/MzMy4dOmSEvzVpWaqhOHDh3P+/PlG97mgoIDDhw8THx+vlMHMzKzOmtDu3bvj5OTE77//zldffcWDDz7IY489BlTlKlywYAHPP/+8EvxVMzU1xcrKiqKiIvr3719rvQMGDODKlSsUFRVxzz33NFpmIbQhD1RCNJ80/Ws6uecIIcSdabXg7/b0DdOmTcPDw4PIyEiSkpKwsrJi9uzZTVrn3LlzNUb8NDExITU1lYiICE6dOkVpaSm2trakpKQoA51o6/Dhw5SVlWFpaalMW7FiBf/85z955JFHCA0NpUePHhrLbNmyhZEjRza67pMnT2Jra1sr+KzLzZs32bt3L6+99hr/+te/au2HpaUlN27c4Pr16xrTz507R0lJCTY2NvWu+4EHHuDgwYN4eno2Wg7RcbVln6qO3v+sI5PAoeOTv5kQQoi21qbNPo8fP46FhYWSl8/X15fNmzc3exteXl4kJCQQFhZGSkqKkr+vqKhIq3x61S5cuMC8efOIjY1VArQ5c+Zwzz33UFZWRmRkJGvXrmXmzJnKMj///DNbtmxh06ZNTS73hx9+yNdff83Fixf58ccfgaraQT8/P1QqFR4eHjz++OP89NNPqFSqBte1Y8cOcnJyOHXqFO+99x4GBgb1zmtubs6FCxeaXF7Rtu40oGrLN+Py8Np+5NgLIYQQnVt2djaLFi2ioqKCgICAWq0Gr127xrx58zh37hy3bt3ipZdeYvz48Q2us82bfdYXzOjp6VFRUaF8LikpaXRdhoaGuLq6smvXLjIzM0lJSQGqAs9r165pVZ7r168zbdo0Zs+ezfDhw5Xp9957LwA9evTA399fo79gXl4eb7/9Nh999BGmpqaNbmPw4MHk5eVRUVGhDCwzffp0nJyclHmq+/zVNGTIEPbt26cx7cyZMxgZGWFsbAz8X5+/3Nxcpk2bxsiRI+tt1llSUkLPnj0bLa9oX/JQ376kNlMIIYQQ7e3WrVtERUXx6aef0rdvX/7+97/j7u7O4MGDlXk2btzIoEGDWL16NZcuXcLLy4sxY8bUaq1YU+PtEFuQtbU1arWagoICADIyMpTvBgwYwLFjxwA4evQoarW61vK9evWiuLhYY1pAQADR0dE4OjrSp08fZTu///57o+UpLS3l1Vdfxc/Pj2eeeUbju+oassrKSrKyshgyZAhQ1bxy1qxZxMXFafQZbIiVlRUODg68//773Lp1C6gKxBrLsjFmzBgOHDjAv/71L6CqKW10dDQvv/xyrXmdnJzw9fXls88+q3d9p0+fVvZDCFE3l0HW9f4T7ePCrwcb/CeEEEJ0NocPH8bKyor77ruPHj164OPjw65duzTmUalUFBcXU1lZSXFxMSYmJnTv3nDdXpv1+XNzcyM0NJSoqCiCg4MxNTXF2dmZkydPAuDp6UlaWhp+fn44OjoqTUNrsrGxQU9PD19fX/z9/QkKCsLBwQFjY2OlySfAiBEjiI2NpbKyEpVKxeHDh5k5cyZXr17l+++/Z+XKlWRkZJCZmcn+/fu5cuUKW7duBf4vpUNoaCiXL1+msrISW1tb3n33XQD++c9/cuXKFeWznp4eqampjR6PRYsWERcXx1NPPUWfPn0wMDAgNDS0wWV69uxJQkIC0dHRvPvuu1RUVODn58fkyZPrnP+VV17B39+fadOmKTWD1crKyvj9999xcHBotKxCCKFLZJAPIYRoGzKKt+4oLCykX79+yue+ffty+PBhjXkmTZrE9OnTcXNzo7i4mBUrVjQ6xki7JnnPycnRGMClOQoLC5kyZQqZmZkaOxsdHY27uzuurq4tUdQmqx6htD2lpqZy5MgRFixYwLfffsvRo0ebPMiOEEIIIUQ1yVUpuqLWSvI+uPQmX3zxhfL5ueee47nnngMgMzOTH3/8kUWLFgGwbds2fv31VyIjI5X5v/76aw4ePMj8+fMpKCjgxRdfZPv27bUqgWpq8z5/LWnbtm2sWLGC8PDwWlFuSEgIhw4daqeSVTVR9fPzU5K8t7V169bx+eefKyN7lpeX89JLL7V5OYQQQgjReUiQ13oa6nPeEOmW0HHVDPZu169fP42UcoWFhcqYJNVSU1MJDg5GpVJhZWWFhYUFv/32G3/961/r3War1vzZ2dkxdOhQ5bOPj0+due20ERgYSHJyMmq1mtzcXK0SvWdlZZGXl8fMmTPZt28fMTExnDhxguXLlyvJ28+ePcusWbO4desW5eXlTJ48mQkTJgCwYcMGkpKSKCgoYO/evcoIovn5+bz11lscPXqUN954Q8lNWN/+VweA7u7ubNmyRVnP7TWfe/bs4YMPPuDmzZtUVlbyxBNP8Oabb7Jy5Uo2b96MmZkZJSUlPPTQQ7zzzjt069aN8PBwRo0ahZeXF1euXCEoKIjnn3+eESNGMGvWLAoKCsjNzeXEiRN8+umnLFmypFnHX4jWIIOrdF41/7at+bdsye1o++Al56YQojORpp6Na62av4hxvvV+V15ejqenJ+vWrVMGfImPj9cYv+Odd97h7rvvZtasWfzxxx+MGzeOtLS0BrMetGrNX13pHporOTkZqArW0tPTtQr+EhMTSUhIAKB///4sXrxYY9ROgHvuuYfk5GR69OhBcXExY8aMwd3dnb59+/Lggw8yatQopkyZorFMnz59iIiIqNXp8nZN2f9///vfvPfee6xZs4ZBgwZRXl6uUQ0cFBTE1KlTqaioYNKkSfzyyy88/PDDyvfXrl1j6tSpPPvss8oQr2lpacqIojY2Npw/f55z587xl7/8RasyCdHa5CG682qrv21LbkfOx//TlvlCheiMar5MsrxxRaevobYqW10v2OS+W7/u3buzYMECXn75ZW7dusX48eMZMmQIn3/+OQATJkxgxowZzJ8/nzFjxlBZWUloaGij6e7apdlndnY2MTExmJqaYm9vz5kzZ1izZg0rV67EyMhIqUkbPXo0q1evxsLCQulDFx8fT35+Pn5+fowbN46dO3cSGRmJnZ0dUFVDuHDhQgwMDNDX11cOgIWFBUCt5qE1h0ItLS3VSDfxwAMP1Fl+c3NzzM3N2bNnT4sdk8TEREJCQhg0aBBQ9QefNGlSrfnKysooKSnBxMREmXbjxg1eeeUVxowZw8SJE+vdxhNPPEFGRgavvPJKi5VbCCFE51Ng1Efj8711z6azbn/IlAdM0dbknGucHKPGPf744zz++OMa06pbKELVIDC3V2w1plWDv9tH/Jw2bRoeHh5ERkaSlJSElZVVkwcgmTt3rkZTSRMTE1JTU4mIiODUqVOUlpZia2tLSkoK9vb2Wq3zv//9L8HBwRQUFBAWFtaqffReeOEFJQC9ceMG1tZVJ/7Jkycb7JO3bt06tm/fzrlz5xg5cqQS7ELVCKV///vfCQoKanDbDg4OfPTRRxL8CSGarTMM9tBWTVI7so5+XDp6+YXQRdo0jW/o2pPrUje0ebPP48ePY2FhoaRy8PX1ZfPmzc3ehpeXFwkJCYSFhZGSkqKkfCgqKmq02rNa//79+eqrrygsLOTVV1/F09OTu+++u9llakhSUlKtPn/aqG72WVZWxmuvvUZGRgY+Pj4APPzww+zatYupU6dibm5e7zrMzc2V/IVCCNEcHSnIq488gLSf5uZl7AznnRAdndw7O4d2afapUqnqnK6np6fR7LKkpKTRdRkaGuLq6squXbvIzMwkJSUFqAo8r1271qRy9e3blyFDhrB//35lQJi2MnjwYI4cOYKtrW2D8+nr6+Pm5sa+ffuU4M/b25sHH3yQV155hc8++6ze4V1LSkowMDBo8bJ3Zs0ZeUtujqKmzlBTJtpe9b2ns91P5Lzv+Or7Xexs56oQnVWbB3/W1tao1WoKCgqwtLQkIyND+W7AgAHs3r0bgKNHj6JWq2st36tXL4qLizWmBQQEEBISgouLC3369FG2s3174yPznD9/nj59+tCzZ0/+/PNPDh482GjzydYwdepUZs2ahbOzMwMHDqSiooKkpCRefPFFjfkqKyvJzc3VaPYJVTWDRUVFzJw5k7Vr12r0Zax2+vRpjRGCWkpnHiVKfszEneps10R76IovYTp6+UXnJeemEB1bm/b5c3NzIzQ0lKioKIKDgzE1NcXZ2ZmTJ08C4OnpSVpaGn5+fjg6OipNQ2uysbFBT08PX19f/P39CQoKwsHBAWNjY6XJJ8CIESOIjY2lsrISlUrF4cOHmTlzJlevXuX7779n5cqVZGRkkJ+fz5IlS1CpVFRWVvLSSy9hY2MDwGeffUZiYiJ//PEHvr6+PP744yxatIiioiLGjx/P9evX6datG0lJSezYsaPBhIqNsbW15a233mLu3LncvHkTlUql0cGzus9feXk5NjY2dQ7sMm/ePObPn09YWBjLly+vNbhNTk4Oo0aNanYZ69MeD7cdpc9ORymn6Do6Yo1SRyprS6l+qSYvD4RoefLbLLqyVs3zp43bc901R2FhIVOmTCEzM1Mj4ImOjsbd3R1XV9eWKGqTVY9Q2p6qy1BaWsrkyZPZtGkT3bu3S2tfIYQQQgjRiXXW1mDtkeevtXRrfBbdtm3bNp599llmz55dq6YrJCSEmzdvtlPJqpqo+vn5UVhY2ObbLigowM/PTxkA5ty5c8ydO1cCPyGEEEKIO3Dh14PNHryos7vX8UHln9BN7V7zJ4QQQgghhGg9DfWdlqavjetMNX/tWg1kZ2fH0KFDlc8+Pj4EBwc3a12BgYEkJyejVqvJzc1lzJgxjS6TlZVFXl4eM2fOZN++fcTExHDixAmWL19ea7TP69ev88wzz/DUU0+xYMECAM6cOcOcOXP4888/eeCBB4iLi6NHjx7k5+fz1ltvcfToUd544w0laX19+7927Vr69u2Lu7s7W7ZsqZUKYs2aNfzxxx9ERETw3//+l/LycgYMGMBHH32EWq3G29ubgQMHUlZWhouLCwsXLkStVjNr1iwKCgrIzc3lxIkTfPrppyxZsqRZx1cIIaDrDL4iScKFEJ2J3MNEtXYN/urKA9hcycnJAJw9e5b09HStgr/ExEQSEhKAqlx/ixcvrjfv3vvvv8/f/vY3jWnLli0jKCgIHx8fFixYwJYtW5g4cSJ9+vQhIiKCXbt2Nbj9puz/P/7xD1xdXXnhhRcAyMvLU76ztLQkLS2N8vJyXnjhBbKysnj66adJS0vDyckJqBoo5/z585w7d46//OUvWm2zIU1t7iDV/0K0ndbsc9FVHiC6yn6Kjk8XBy9pzksibdXcx5auzeqs/dWEqEknO4BlZ2cTExODqakp9vb2nDlzhjVr1rBy5UqMjIyUmrTRo0ezevVqLCwslIFN4uPjyc/Px8/Pj3HjxrFz504iIyOV1AiBgYEsXLgQAwMD9PX1lVo2CwsLgFr9BgGOHDnCxYsXcXNz48iRI0BVyoWff/6Z+Ph4AMaNG8eqVauYOHEi5ubmmJubs2fPnhY7JhcuXODRRx9VPteVD7B79+44OTnx+++/17mOJ554goyMDF555ZU7Lo/cFIVoX9q+gLl9Prl2hehcdCXgq6mtytTS25H7o+gK2jX4uz0VxLRp0/Dw8CAyMpKkpCSsrKyYPXt2k9Y5d+5cjdFDTUxMSE1NJSIiglOnTlFaWoqtrS0pKSnY29s3ur6KigpiY2OJi4tj7969yvTLly/Tu3dvZQCVfv36tcjALi+88IISgN64cQNr66ob26RJk3jjjTfYsGEDrq6u+Pv707dvX41lb968yd69e3nttdfqXLeDgwMfffRRiwR/2tL27Z8u/ngJocvkIaVz0TaYl7+7EEKIO6FzzT6PHz+OhYWFkuPP19eXzZs3N3sbXl5eJCQkEBYWRkpKipILsKioSKn1a8imTZsYOXIk/fv3b3RelUrV7HJWS0pKqtXnD6pyJGZlZfHDD/+fvTsPi7LeH///HEdElkLAXILwpx4DBNQUMzHMA5LkwqTGJ21xyUIsPFmQkoZHSTH0KJrFQaWU8qhHBaVATDGXFiVNjwpKx0hCNEElU9FYZH5/8OU+jGwDsgzwelyX1+XM3Pf7ft83M/d9v+738vqGQ4cOMXbsWBISEoD/zeypUqnw9PTUyQ9YnrW1Nbm5ufddx9qQoK7xyVglIRpWQ3QNM7SgzhC7EgphKJriYU1rGW8tGp5BdvusKohSq9WUlJQorwsKCmosy8TEBDc3N/bt20dSUhKxsbFAaeB58+bNGtc/ceIEP/74I5s3byY/P5+ioiJMTU0JDAzkxo0bFBcX07ZtWy5fvkynTp303MO66dChA2PGjGHMmDFMnz6do0eP4uTkpIz5q0lBQQHGxsYNWse6qMtNhvTLr5qc7A2X3FC3DK3hnHO/38+63BxXdXMrvxVhaMq+t405g6b8DkR9Mbjgr0ePHmRnZ5OVlYWdnR2JiYnKZzY2Nhw4cACAtLQ0srOzK6xvZmZGfn6+znu+vr74+/vj6upKhw4dlO188UXN07aWjekDiIuLIzU1laCgIAAGDRrEV199xahRo9ixYwceHh613V29HT58mH79+mFiYsKtW7fIysrSqzWyvMzMTHr16tVANay7upzQWsPNl2h55OItWou6nKOby++juoc4EsC2LvJ3Fc2RQY35c3d3JygoiNDQUPz8/LC0tGTAgAGcO3cOgBEjRhAfH49Go8HFxUXpGlqevb09arUaHx8fxo0bx5QpU3B2dsbc3Fzp8gkwcOBAwsPD0Wq1qFQqTp06RUBAADdu3GD//v2sXr1aJ/CszDvvvMNbb73FypUrcXR0xNfXFyjtUjp+/Hhu3bpFmzZtiImJYdeuXZibm9f5WKWlpfH++++jVqvRarX4+vrSp0+fSgPgqqSkpDBs2LA616E8acEQDa2mlgN5ACCEaArVXfPkeiiEMHQGn+S9fK67usrJyWHSpEkkJSXpzOa5aNEiPDw8cHNzq4+q1lrZDKWNsY3CwkJeeuklNm3apExS0xjKbuDlRl00tLIHEnLzJYQQojpybyJqS5K8NyM7d+4kIiKC4ODgCmkc/P39OXnyZBPVrLSLqkajUZK816esrCxmzpyJtbU1AJcuXSIwMLBRAz+QE6toPBL0Va42OTnl9yqEaA3kXCdas0YP/hwdHXn00UeV16NGjcLPz6/K5QcNGsSgQYMq/WzChAls2bKF7OxsTpw4UWli92effZZnn31WeZ2cnEx6ejoBAQGcP3+ejz76iJkzZ7JixQq8vb111r116xbPPPMMXl5ezJ8/Hygde7d06VKKiopwcnJi8eLFSkCVkpJCWFgYxcXFWFpasnHjxir3f+3atXz77bd4eHhgZGQElHZZnTp1KsHBwQB88skn3L59m7Zt27J7924A/vvf/yrHb/z48bi7uxMWFkZmZiZt27bl0UcfJSQkhNzcXIqKimjfvj0A58+f5/Tp01UeSyFEyyQ3OUKIxiazTrcu8vduXho9+KssvUNdbdmyBYCLFy+SkJBQafB3r+joaCIjIwHo2rUrS5YsUdIp3GvlypU8/vjjyuuSkhKCg4PZsGED3bt3Z9WqVezYsQNfX19u3LjBwoULiY6O5uGHH+batWuVllnd/rdr1449e/bg5+enk4ZixowZzJgxAyjtxlm2fkFBAWPGjCE4OFiZbObIkSPk5eXh6urK2rVr8ff3B2DYsGGsWrWK1157DRMTkxqPkxDNTW1auO5VHwGSjIMVQjTUhC/3nt8M/aGOnAMNW30Ha/L3bl4MptvnoUOHCAsLw9LSEicnJy5cuMCaNWtYvXo1pqamTJs2DYDRo0cTFRWFra2tMp5t+fLlZGRkoNFoGDt2LHv27CEkJARHR0egtIVwwYIFGBsbY2RkpARWtra2ABW6gwKkpqZy7do13N3dSU1NBeD69eu0a9eO7t27AzBkyBDWrFmDr68vX375JV5eXjz88MMASnfL2mjbti3PP/88MTExvPXWWzUu/+WXX9KvXz+dWUafeOKJSpdVqVQ8/vjj7N+/n5EjR9a6bqL5qC4IMvQbhvvR1PsmFz8hRHn1eU5oqPNbVQ+tpCWn5Sl/b+Dagu8FRM0aPfi7d4bP6dOn4+npSUhICDExMXTr1o1Zs2bVqszAwECdSWEsLCyIi4tj3rx5nD9/nsLCQhwcHIiNjcXJyanG8kpKSggPD2fp0qUcPnxYed/S0pLi4mJOnz6Ni4sLu3fv5vLly0BpGoXi4mJefvll8vPzmTRpkk53U329+OKL+Pj48Oqrr9a47Llz5/TanzLOzs78+OOPrTb4ay25AVvyvgn96NMKWt33pLX8VoRhaQmt51XV21Bb7qqqb3M9/qJqhvKdE03PILp9nj17FltbWyV1g4+PD1u3bq3zNry9vYmMjGT27NnExsYqKR6uXLmi052yKps2bWLo0KEV8uipVCpWrFjBkiVLKCwsZMiQIajVagDu3r1LWloaGzZs4M8//2TChAn07dtXaSXUl7m5ORqNhs8++0wZr1dfrK2tyc3NrdcyDZ3OzUQTn/jkhlo0lvv9fsn3UzSFxgo4qkvMXaa6/H2Sm1YI0ZwZTLdPlUpV6ftqtZqSkhLldUFBQY1lmZiY4Obmxr59+0hKSiI2NhYoDTxv3rxZ4/onTpzgxx9/ZPPmzeTn51NUVISpqSlBQUE89thjbNq0CYBvv/2WzMxMALp06YKlpSWmpqaYmpri6upKenp6rYM/gMmTJzNu3DidvISV+ctf/sLRo0f1LregoABjY+Na16c5M6Snl3LxF0KIpleX64IhXUtE89ASWrJFy2QQwV+PHj3Izs4mKysLOzs7neTqNjY2HDhwAChNdF5ZUnMzMzPy8/N13vP19cXf3x9XV1c6dOigbOeLL2rO07F8+XLl/3FxcaSmphIUFATAtWvXsLa2prCwkHXr1ikTqnh6ehIaGkpxcTFFRUWcOnWKKVOm1OYwKDp06IC3tzfbt29n/PjxVS43ZswY1q5dy4EDB5Tk7YcOHaJz587Y29tXWD4zM1NnplVRd/o8Oa6MXACEoWqtY0WFEKIhyPVeGKomH/Pn7u5OUFAQoaGh+Pn5YWlpyYABAzh37hwAI0aMID4+Ho1Gg4uLi9I1tDx7e3vUajU+Pj6MGzeOKVOm4OzsjLm5uU7r2cCBAwkPD0er1aJSqTh16hQBAQHcuHGD/fv3s3r1ap3AszLR0dEcOHCAkpISJk6cyODBgwHo2bMn7u7u+Pj40KZNG5577rn7CrReeeUV/vWvf1W7TPv27YmKiiIsLIywsDDatm2Lvb098+bNq3T5lJQU3n777TrXSfyPnNRFS5sQQQI8IZpeZQ9h5LcphKhPKq1Wq63qw/fff7/K7pgA7733XoNUKiUlRWcCl7rIyclh0qRJJCUl6czmuWjRIjw8PHBzc6uPqtZa2QyljSE7Oxt/f38SEhK4evUqgYGBxMTE1KqMqrotNNT4tYaaJtsQ1KW1sCXsd2tUl99Hc+kiJGNXhRCiZdH33kuf61RzuZbV1uIdNfccrIt5Y30apNzqVNvy5+zsDMDx48f5+eeflVkid+/eXatZJhvbzp07iYiIIDg4uEIaB39/f06ePNlENSvtoqrRaFi7di2dO3dusO0cO3aMhQsXYmlpCcClS5eU5PG1UdUPt6Fu+lrSieJeLXnfWpK65gss/5uoy++juXw/JOATQoiWRd/rjz7LNZdrWWtWbctfmZdffplPP/0UIyMjAIqKinjllVf4/PPPG7yCQrQULfVpmBBCCNGSteReSUI/rablr0xubi75+fnKxCm3b99u8JQBjo6OOmPmRo0ahZ+fX53KmjBhAlu2bCE7O5sTJ04wZsyYGtdJTk4mPT2dgIAAjh49SlhYGD/99BMrVqzA29u70np27dqVqKgoAIKDg/nhhx944IEHAPjggw9wdHQkOjqaL7/8EihND5GRkcHhw4eVY3tvuWUthB4eHmzfvh0rKyuuXLlCWFgYp0+fpl27dtjY2DB37lyMjIyUbp7Hjh1j/vz5tGnThoSEBPbv38/p06f529/+VqdjKO6fXCSEEEKIpldVD4+qejbI9Vu0JHoFf35+fowdO5ZBgwYB8MMPPzBz5swGrVhl+QDrasuWLQBcvHiRhIQEvYK/6OhoIiMjgdKgbsmSJXz66ae1qufs2bN1AkWAV199VUng/vXXX7Nhw4YKgV915Wq1WgICAnj22WeJiIgASvMkXrt2jS5duijLubq6snbtWmU20mHDhrFq1Spee+01TExMatx/IUT9kxk1hTAsLW3iJqEfOd+K1kyv4G/8+PEMHTpUGSsXGBjIQw891KAVq8qhQ4cICwvD0tISJycnLly4wJo1a1i9ejWmpqZMmzYNgNGjRxMVFYWtra0yycry5cvJyMhAo9EwduxY9uzZQ0hICI6OjkBpC+GCBQswNjbGyMhISQhva2sLUGH84P1KTExk9OjRtVrnyJEjtG3blokTJyrvldW/sjQYZVQqFY8//jj79+9Xxm4KIRqX3HAYNpnMpvWRYK9pyXAIIRpftcFfRkYGPXv2JC0tDShtAYPSbqC5ubkNOunLvSkhpk+fjqenJyEhIcTExNCtWzdmzZpVqzIDAwN1ZhG1sLAgLi6OefPmcf78eQoLC3FwcCA2NlbvfSsoKGDcuHG0bdsWPz8/hg8frnwWERHBxx9/zODBgwkKCqJdu3bKZ3fu3OGbb74hJCSkVvtw7ty5Oh93Z2dnfvzxx2YV/JVdGOSi0PD0nY1U/hal7m3Fk2Ch+ZO/oRB1V5eeDXI9EaLxVRv8bdiwgffff58PPvhAea986ofPPvuswSpWWbfHs2fPYmtrq+T68/HxYevWrXXehre3N5GRkcyePZvY2FglJ+CVK1eUVr+a7N+/n86dO3PhwgUmT57Mo48+ip2dHW+//TYPPfQQRUVFhISEsHbtWgICAnTW69+/f6VdPhuKtbV1g4/VrG8t9cJQ34FDfQxGb6nHuqFIoCCE0FdreFjUEvdJ3B/pVm2Yqg3+3n//fQAmTpzI0KFDMTc35+OPP+bMmTO8/vrrjVLBe1WVd1CtVlNSUqK8LigoqLEsExMT3Nzc2LdvH0lJScTGxgKlgefNmzf1qk9ZuoZHHnmExx9/nDNnzmBnZ0enTp0AaNeuHePGjaswXjAxMZFRo0bptY3yevXqxVdffVXr9aD0mBgbG9dpXVG/6vsiKSdU0dLUR8oNIQyFfC9FayT3JoZJr0Fs//znPzE3N+fYsWN8//33jB07lgULFjRw1Srq0aMH2dnZZGVlAaUBVBkbGxvOnDkDQFpaWqXj38zMzMjPz9d5z9fXl0WLFuHi4qK0wvXo0YNff/21xvr88ccfFBYWApCXl8fx48f5y1/+AqC0sGm1WpKTk+nVq5ey3s2bNzl69Cienp767rriiSeeoLCwUKfF89SpU/zwww81rpuZmakzg6oQQhiqTi796/SvOTmW8YvyTwghhGgMek34olarATh48CATJkxg+PDhfPTRRw1asXvH/Lm7uxMUFERoaCh+fn5YWloyYMAAzp07B8CIESOIj49Ho9Hg4uKidA0tz97eHrVajY+PD+PGjWPKlCk4Oztjbm6udPkEGDhwIOHh4Wi1WlQqFadOnSIgIIAbN26wf/9+Vq9eTWJiIhkZGfz9739HpVKh1Wp57bXXlOAvKCiI33//Ha1Wi4ODAwsXLlTK37t3L0OGDMHU1FTv41FcXEy7du1QqVR89NFHhIWFsXbtWoyNjZVUDzVJSUnh7bff1nubwvDo072zuhtJeQrX+PRtwWqswEXG0RoO+RsI0bI01qRRdXlgJOcbUUavJO/Tp0+nc+fOfP/998TFxdG+fXuee+45vviiYRIe6islJUVnApe6yMnJYdKkSSQlJenM5rlo0SI8PDxwc3Orj6rWWtkMpVDaqqjRaPjmm29qVUZ2draS9+/q1asEBgYSExPTENUVQghRBXkgI4QQzVurS/K+cuVKvvnmG1555RUefPBBcnNzmT17dkPXrcHt3LmTiIgIgoODK6Rx8Pf3V1JbNAUzMzM0Gg1Tp04lKiqKwMDAWq1/7NgxFi5ciKWlJQCXLl0iODi4IaoqhBCiGhLgCdG81cekas2FofVWEfVPr5a/xubo6KgzNm3UqFH4+fnVqawJEyawZcsWsrOzOXHihF4J3pOTk0lPTycgIICjR48SFhbGTz/9xIoVK3SStl+6dIn33nuP3377DZVKxdq1a7G1tWXjxo3ExMSQlZXF4cOHlZlDU1JSeP3115W8gV5eXjozgN67/2vXrqVz5854eHiwfft2rKysSE1N5W9/+xsfffQRjzzyCO+//z7Hj5f+UPv3709ISAgPPPAAWVlZzJw5k6ysLE6cOMFPP/3E+vXrdWZuFbUj+YiEEEIIIVqfVtfy19gqS/NQV1u2bAHg4sWLJCQk6BX8RUdHExkZCZTmNlyyZEmF2ToB5syZg7+/P0OGDCE/P19pPezfvz/Dhg1j0qRJFdZxdXWtsZtqVfufnp7O3/72N1auXEnv3r3529/+Rq9evVi6dCkAH374IfPmzePDDz/Ezs6O+Ph4HnvsMaB0vOPly5e5dOkSDz/8cI3HQFQkAZ+oT9IVUIjWo6bWlLJWlNaQEkII0bQMMviryqFDhwgLC8PS0hInJycuXLjAmjVrWL16NaampkybNg2A0aNHExUVha2trTJ2bvny5WRkZKDRaBg7dix79uwhJCQER0dHoLSFcMGCBRgbG2NkZKS01pW10t3bLfTnn3+muLiYIUOGAKXdNMv07t273vf9l19+Yc6cOSxdupQ+ffrw66+/kpqaSkREhLLMG2+8gZeXF1lZWdjZ2VUo469//SuJiYm89tpr9V4/IUTNyt/Yubawmzq5aRVV0Xdyipb80EPf30OWaQfd9apYrrYTftT22MrvWYiWyyCDv3tn+pw+fTqenp6EhIQQExNDt27dmDVrVq3KDAwM1JkcxsLCgri4OObNm8f58+cpLCzEwcGB2NhYnJycaiwvMzOTBx98kICAALKzsxk8eDBBQUHKzKhV+c9//oOPjw+dOnVizpw5OikgqvP666+zbNkyXF1dgdLg09HRUWd7arUaR0dHzp07V2nw5+zszLp16yT4E8IANdYscQ2lsepc15tS6bbddFrT8b7f37G+x6qhj2lzPAcJIfRjkMFfZd0ez549i62trZLCwcfHRyfXXW15e3sTGRnJ7NmziY2NVVI9XLlyRWn1q05xcTHHjh1j586ddO3albfeeou4uDh8fX2rXMfJyYmvv/4aMzMzDh48yBtvvMGePXv0qu/gwYPZtm0bTz75JGq1WklDca+q3gewtrZW8g8K0dI0hxQG1d1Qyc2Wfup6nAz5e2EIpHWufsjvWOhDHkaJpmSQwV9Vqgpq1Go1JSUlyuuCgoIayzIxMcHNzY19+/aRlJREbGwsUBp43rx5s8b1u3TpQu/evXnkkUcA8PT0rHF2UHNzc+X/Tz31FAsXLiQvL0+vYHP+/Pn8/e9/Z+HChYSGhtKrVy/OnDlDSUmJ0iW1pKSE9PR0evbsWWkZBQUFGBsb17gtIZojuYAKQ9XUrbr6zN53b18RCWKEaDhyvRJNqdkEfz169CA7O1sZz5aYmKh8ZmNjw4EDBwBIS0sjOzu7wvpmZmbk5+frvOfr64u/vz+urq506NBB2Y4++QtdXFz4448/lOAtJSUFZ2fnate5cuUKHTt2VBLHl5SUKKkYaqJSqVixYgXTpk1j1apVvPnmm/Tu3ZvIyEhlxtDIyEicnJzo1q1bpWVkZmbq3c1UiObq3haMqi6yrWnqbtG0mjqQunccWWXke98yNPZ5rakfbAghas8gg797x/y5u7sTFBREaGgofn5+WFpaMmDAAM6dOwfAiBEjiI+PR6PR4OLionQNLc/e3h61Wo2Pjw/jxo1jypQpODs7Y25urnT5BBg4cCDh4eFK98lTp04REBDAjRs32L9/P6tXryYxMRG1Ws2cOXOYPHkyUNqls6zL52effUZ0dDRXr17Fx8eHp556isWLF/PVV1+xefNm1Go17du3Z8WKFVW2ZlamXbt2REZG8tJLL9GxY0cWL17M+++/j5eXF1qtln79+rF48eIq109JSWHYsGHVbkNmIGx6kmOnbmrb7VO+z6K1kO967TXXCU8a+2/dFMelui6T0n1ZiJoZZJ4/faSkpOhM4FIXOTk5TJo0iaSkJJ3ZPBctWoSHhwdubm71UdVaK5uhtD7LKiws5KWXXmLTpk20bWuQMb8QQgghhMGRoFJInr8WYOfOnURERBAcHFwhjYO/v3+N4/cakpmZGRqNRknyXhdlSd6tra2B0oT0gYGBEvgJIZqFqp7u69utV7RM8vcXTUG+Z6IlabYtf0KI5q+2uarKk4uxMGRVdd9uLt0HhRBC/I+0/OnJ0dGRRx99VHk9atQo/Pz86lTWhAkT2LJlC9nZ2Zw4cYIxY8bUuE5ycjLp6ekEBARw9OhRwsLC+Omnn1ixYgXe3t7KcpcuXeK9997jt99+Q6VSsXbtWmxtbTl8+DBLly6lqKgIJycnFi9eTNu2bfniiy9Yt24dUNpKt2DBAhwcHKrc/7IWPA8PD7Zv364zu2dcXBzvvvsuGzZsYPDgwQDs3buXgIAAVq1ahbe3N0VFRaxatYo9e/bQrl072rdvz8yZM3nqqacAOHPmDGPHjiU6Ohp3d3egdNzk888/T0ZGBocOHQLgnXfe4ZNPPqnT8ReiIVTXonPv56JhyXjf+tUYQV5dHp7I31IIIVq3Bg3+KsvXV1dbtmwB4OLFiyQkJOgV/EVHRxMZGQlA165dWbJkCZ9++mmF5ebMmYO/vz9DhgwhPz+fNm3aUFJSQnBwMBs2bKB79+6sWrWKHTt24Ovri62tLRs3bsTCwoKDBw8SEhLCtm3bKpSr7/4/+uijJCQkKMFfYmKiTjC5atUqrly5QkJCAu3atePq1av88MMPyucJCQkMGDCAxMREJfgr27aHhwcAVlZWdOrUiR9//JEBAwbUWCchGpvclDauunafk7EvhkOOsRCiIUk365apSQaAHTp0iLCwMCwtLXFycuLChQusWbOG1atXY2pqyrRp0wAYPXo0UVFR2NraKhOXLF++nIyMDDQaDWPHjmXPnj2EhITg6OgIlLYQLliwAGNjY4yMjJRWNltbW4AK4/t+/vlniouLGTJkCFDakgeQl5dHu3bt6N69OwBDhgxhzZo1+Pr60r///57o9uvXj8uXL9/X8XB1deXYsWMUFRVRWFhIVlaWsj937txh27Zt7Nu3j3bt2gHQsWNHRo4cCZQmdf/qq69Yv349L7zwQrW5/Dw9Pfnyyy8l+BOVkqSzpZrrLH+1Vde/cWv+bgj9VZUCoLX8voRoCe73fC/B4/07dOgQixcvpqSkBF9f30p7UKakpBAWFkZxcTGWlpZs3Lix2jIbNPi7N2XD9OnT8fT0JCQkhJiYGLp168asWbNqVWZgYKDOLJ8WFhbExcUxb948zp8/T2FhIQ4ODsTGxuLk5FRjeZmZmTz44IMEBASQnZ3N4MGDCQoKwtLSkuLiYk6fPo2Liwu7d++uNMjbvn07Q4cOrdU+3EulUuHm5sa3337LzZs38fDwUHIV/vrrr3Tt2lUnQXx5P/74I7a2ttjZ2TFo0CAOHjzI008/XemyLi4urFq16r7qWhl9WgLkB2/45G9USt+b0eZ+UWvu9Rf1q76/D1X9jhoy2JOcc6Ila473WoZWn+bm7t27hIaGsn79ejp37sxzzz2Hh4cHf/nLX5Rlbty4wcKFC4mOjubhhx/m2rVrNZbb6N0+z549i62trZKLz8fHh61bt9Z5G97e3kRGRjJ79mxiY2OVnH1XrlzRGVtXleLiYo4dO8bOnTvp2rUrb731FnFxcfj6+rJixQqWLFlCYWEhQ4YMQa1W66x75MgRtm/fzqZNm+pc/zKjRo3is88+49atW8yZM0fvFBaJiYmMGjUKgJEjRxIfH19l8GdlZUVubu591/Ve8uMWrVFz/9439/qL+tUSvg/1GfBVFwwbci8JQ3moIy289c/Qvmui4Z06dYpu3brxyCOPAKWxwr59+3SCvy+//BIvLy8efvhhAGWW/+o0SbfPqhKbq9VqSkpKlNcFBQU1lmViYoKbmxv79u0jKSmJ2NhYoDTwvHnzZo3rd+nShd69eysH1tPTU0nz8NhjjymB3bfffktmZqayXnp6Ou+99x7r1q3D0tKyxu3UpE+fPpw7d4727dsrXU0BunXrxm+//catW7cqtP7dvXuXPXv28PXXXxMVFYVWq+X69euVLgtU2yW0oeibsLyMXCCEMGy1/U2D/K5bI0MOkPRRXZ0NeX8aqm61nlzItIPOy071V5VGI+c60Rj+/e9/8+9//1t5/fzzz/P8888DpfnIu3TponzWuXNnTp06pbN+ZmYmxcXFvPzyy+Tn5zNp0iSeffbZarfZ6MFfjx49yM7OJisrCzs7OxITE5XPbGxsOHDgAABpaWlK18fyzMzMyM/P13nP19cXf39/XF1d6dChg7KdL76oeVpWFxcX/vjjD/Ly8rCysiIlJQVnZ2cArl27hrW1NYWFhaxbtw5/f3+gdHbQmTNnsnTpUp1A7X69/fbbFYIzExMTxo8fz+LFi1m4cCHt2rUjNzeXw4cPY2VlhYODg84MnnPmzCE5ObnSP3xmZia9evWqt/rqQ06EQl+G8sRaVE9+00If8vttWVrj39OQz3XN/eGK+J/ywd69KsvGd28D2t27d0lLS2PDhg38+eefTJgwgb59+1YbnzTqmD93d3eCgoIIDQ3Fz88PS0tLBgwYwLlz5wAYMWIE8fHxaDQaXFxclK6h5dnb26NWq/Hx8WHcuHFMmTIFZ2dnzM3NlS6fAAMHDiQ8PBytVotKpeLUqVMEBARw48YN9u/fz+rVq0lMTEStVjNnzhwmT54MgJOTE76+vkDpbKEHDhygpKSEiRMnKrNxfvzxx1y/fp2FCxcCpS2WcXFxeh0THx8fZdKZZ555Bnt7e+WzstQN95o1axYrV65k1KhRGBsbY2Jiwt/+9jcSExMZPny4zrJPP/00mzdvrjT4S0lJYdiwYXrVU9SdnJTrRo6VEE2nPh6+VHXukzQiQtQv+d20Dl26dNGZbyQnJ4dOnTpVWMbS0hJTU1NMTU1xdXUlPT292uCvyZO8p6Sk6EzgUhc5OTlMmjSJpKQkndk8Fy1ahIeHB25ubvVR1Vorm6G0KZXPLfjiiy8SGRmJhYVFk9ZJCCGEEEIYnuq6uxpya2hDa4ok78XFxYwYMYINGzYoE74sX75cpxdfRkYGoaGhfPLJJxQVFSlzlpTPs36vJhnzV5927txJREQEwcHBFdI4+Pv7K+P3moKZmRkajUZJ8t6YypK8FxUV0aZNG/Ly8pg6daoEfkKIZkeSmQshRONozQGeoWnbti3z58/n1Vdf5e7du4wfP55evXqxefNmACZOnEjPnj1xd3dXehY+99xz1QZ+0IQtf46OjjqVGzVqVKW5K/QxYcIEtmzZQnZ2NidOnNArAXxycjLp6ekEBARw9OhRwsLC+Omnn1ixYgXe3t5A6WyeS5YsUdb55ZdfiIiIYPjw4QQHB/PDDz/wwAMPAPDBBx/g6OhIdHQ0X375JVDaDzcjI4PDhw8rYxHv3f+ywNDDw4MuXbrozByq0Wi4e/cuCQkJynuLFi3iq6++4uDBg5w7d47Zs2cD8Ntvv2Fubs4DDzyApaUloaGhzJw5k6ysLE6cOMFPP/3E+vXr+eCDD+p0jIVhk66mVasqcJDjJIQQ4n7IWPXWoyla/hpKk7X8VZYGoq62bNkCwMWLF0lISNAr+IuOjiYyMhKArl27smTJEj799FOdZZ544gmljtevX+fpp59WksEDzJ49WwkUy7z66qu8+uqrAHz99dds2LChQuAHle9/fn4+v/32G127diUjI6PCOiUlJSQnJ9O1a1eOHj3KoEGDlDKCg4MZNmyYTn3i4+N57LHHgNKxkpcvX+bSpUvKdLCidgx53EpTb9+QybERdVHTTH/N9em4vq2o8rsRompl5we7St5vrucG0XoYXLfPQ4cOERYWhqWlJU5OTly4cIE1a9awevVqTE1NmTZtGgCjR48mKioKW1tbZWzd8uXLycjIQKPRMHbsWPbs2UNISAiOjo5AaQvhggULMDY2xsjISMkDaGtrC1Ch22h5X331Fe7u7piYmOi9L4mJiYwePVrv5Z955hl27drFtGnTSEhIYNSoUTozlqakpNCrVy9GjhxJYmIigwYN0rtsgL/+9a8kJiby2muv1Wo9UUpuhoRoeo31EKal3sDJeUyI+9dSzw+idWiy4O/emUCnT5+Op6cnISEhxMTE0K1bN2bNmlWrMgMDA3Umj7GwsCAuLo558+Zx/vx5CgsLcXBwIDY2Ficnp1qVnZiYyNSpU3Xei4iI4OOPP2bw4MEEBQXRrl075bM7d+7wzTffEBISovc2RowYwbvvvsu0adPYv38///jHP3SCv7KAcPjw4axYsYKioiKMjIz0Lt/Z2Zl169ZJ8GcA6jKGCeTGrS5qe6zlGBs2+fvUnj5dn/XNaSY3vUKI+lB2XpJzeuMzqG6fZ8+exdbWVknx4OPjw9atW+u8DW9vbyIjI5k9ezaxsbFKKogrV64orX76yM3N5b///S9PPvmk8t7bb7/NQw89RFFRESEhIaxdu5aAgADl8/3799O/f/9Ku3xWxcLCggcffJDExER69uxJ+/btlc8KCws5ePAg7777Lubm5vTt25fvvvuuVqkbrK2tyc3N1Xt50XDkZNd4DPVY33uzbag31dWNaZGxps2DPn8bQ/3+tRTN5ffe2hjacI7WNIawJe+boTO4bp/3Ji8so1arKSkpUV4XFBTUWJaJiQlubm7s27ePpKQkYmNjgdLA8+bNm3rXKSkpCS8vL51WtrI8G+3atWPcuHEVxgsmJiYyatQovbdRZuTIkYSGhupMNAPwzTffcOvWLXx8SgeG3rlzh/bt29cq+CsoKKiQRF6I2qqqhUBuZmqnuRyv6i7QcvEW9akhJ2dq6omfmsvvvYyhBSHlrzv1eSyber/uVZ/5NetKHuq1fAYV/PXo0YPs7GyysrKws7MjMTFR+czGxoYDBw4AkJaWRnZ2doX1zczMyM/P13nP19cXf39/XF1dlVa4Hj166HSnrEliYiJvv/22znu5ubl06tQJrVZLcnKyTs6NmzdvcvToUZYtW6b3NsoMHz6c3NxcnnzySZ1WusTERBYtWqSMIbx9+zaenp7cuXNH73GImZmZOvVsCE19gRUNr7ndxAghmoeGvE7INah2DO14yXWnavX9tzK0v72ofwYz5s/d3Z2goCBCQ0Px8/PD0tKSAQMGcO7cOaB0PFx8fDwajQYXFxela2h59vb2qNVqfHx8GDduHFOmTMHZ2Rlzc3OlyyfAwIEDCQ8PR6vVolKpOHXqFAEBAdy4cYP9+/ezevVqJfDMzs7mt99+4/HHH9fZVlBQEL///jtarRYHBwcWLlyofLZ3716GDBmCqalprY+Lubl5hZQXd+7c4dtvvyU0NFR5z9TUlAEDBrB//35GjhypV9kpKSm1aimsCzlpCCGEaGkaquVJCCEaW5Pl+dNHSkqKzgQudZGTk8OkSZNISkrSmc1z0aJFeHh44ObmVh9VrbWyGUobazuFhYW89NJLbNq0ibZt7z/mlwuhEEKIlkYmoRCtQX13663LJHbN7Tcmef6aiZ07dxIREUFwcHCFNA7+/v6cPHmyiWpW2kVVo9EoSd7rW1ZWFjNnzsTa2hqAS5cuERgYWC+BH9x/wCe5pkRjaagHFYY2JkaI5sjQhgrI79gwyQPn+iVdRVu3Rmn5c3R05NFHH1Vejxo1qkLXRn1NmDCBLVu2kJ2dzYkTJ/RK6J6cnEx6ejoBAQEcPXqUsLAwfvrpJ1asWKGTFH3p0qUcPHiQkpIShgwZwrx583QmoHn//feJi4tTWuyio6P58ssvAbh79y4ZGRkcPny4wgyfZftfFuh5eHjQpUsXNm3apCyj0Wi4e/cuCQkJpKSkMGnSJBYtWoSvry8AZ86cYezYscyePZtp06YRHBxMUlIS3333Hebm5kBpa+bnn3/O4cOHMTU15fnnnycjI4NDhw4B8M477/DJJ5/U4ajrrzU8/RGiJoY2g5wQQggh6k5a/mqpsrQOdbVlyxYALl68SEJCgl7BX3R0NJGRkQB07dqVJUuWVJid8/jx4xw/flyZCOaFF17ghx9+UBKpnz59mhs3buis8+qrr/Lqq68C8PXXX7Nhw4ZKUztUtv/5+fn89ttvdO3alYyMjArrPProoyQlJSnBX2JiIg4ODjrL2NnZsW/fPjQaDSUlJaSkpCitiGXb9PDwAMDKyopOnTrx448/MmDAgBqPWV3de2Nb9rROntSJ1kQCPNGS1Ofsf4bwYKS6/Wmobp/VpXqQVi0hRGNq0m6fhw4dIiwsDEtLS5ycnLhw4QJr1qxh9erVmJqaMm3aNABGjx5NVFQUtra2yhi25cuXk5GRgUajYezYsezZs4eQkBAcHR2B0hbCBQsWYGxsjJGRkZLXz9bWFqBCN1CVSkVhYSFFRUVotVqKioro2LEjUNqqt3TpUpYvX05ycnKl+5KYmKjMxKmPZ555hl27djFt2jQleXv5GUgffvhhbt26xdWrV7G2tuabb77hqaee0ilj9OjRJCUlodFoSElJoX///nzzzTdVbtPT05Mvv/yyQYO/e8mFTAghas+QUqrUZyBkCA9GmiJ9SXV/N7lOCiEaU5uaF7l/ZTN7lv3btWsXBQUFhISEEBUVxaZNm7hy5UqtygwMDMTV1ZX4+HimTJmCr68vcXFxAJw/f57CwkIcHBw4fvw4Tk5ONZb32GOPMWjQIJ588kmefPJJ3N3d6dmzJwAbN27E09NTye13rzt37vDNN9/w9NNP613/ESNGsHfvXqA0IXxZC929y+zevVvZh3bt2ul83q1bN/Ly8vjjjz/0yivo4uLCjz/+qHcdhRBCNI1OLv0r/Sca1rGMX+o0fEEIIZqLJuv2efbsWWxtbZWUDT4+PmzdurXO2/D29iYyMpLZs2cTGxurpHa4cuWK0upXnV9//ZWMjAwOHjwIwCuvvMLRo0exs7Nj9+7dfP7551Wuu3//fvr3719pl8+qWFhY8OCDD5KYmEjPnj1p3759hWWeeeYZ3nrrLX755RdGjRpV6eygXl5eJCYmcvLkSZ1UEJWxsrLSyR0ohDAcVXX9qq67WEvSWvZTND1D6Hpan6TbqDBUMjGaYWrSbp/lJ1MpT61WU1JSorwuKCiosSwTExPc3NzYt28fSUlJxMbGAqWB582bN2tcf+/evfTt2xczMzOgNO/gf/7zH/Lz88nKylJa9e7cuYOXl5fSagfo1epWmZEjRxIaGsqSJUsq/fyhhx6ibdu2fPfdd8ybN6/S4G/UqFGMHTuWsWPHVujKeq+CggKMjY1rXU8hRMOr6qatudzMVdVNsSZl+9dc9lPUXn2OGawPhlCH+iS/nZrJw6Wm0dJ+ay1FkwV/PXr0IDs7m6ysLOzs7JSk6gA2NjYcOHAAgLS0NLKzsyusb2ZmRn5+vs57vr6++Pv74+rqqrTC9ejRQ2csXVUefvhhtm7dSnFxMVqtlqNHjzJ58mSGDRvGd999pyz32GOP6QR+N2/e5OjRoyxbtqw2uw/A8OHDyc3N5cknn6yyRe5vf/sbeXl5qNXqKuv91ltv6ZWvMDMzk169etW6nkIIURO5mRJVkRtA0RR0Wp1MO+h8VvkgHiFah0YJ/srG/JVxd3cnKCiI0NBQ/Pz8sLS0ZMCAAZw7dw4oHesWHx+PRqPBxcVF6Rpanr29PWq1Gh8fH8aNG8eUKVNwdnbG3Nxc6fIJMHDgQMLDw9FqtahUKk6dOkVAQAA3btxg//79rF69msTEREaMGMGRI0cYM2YMKpUKd3f3Ssfh3Wvv3r0MGTIEU1PTWh8Xc3PzGlNe9O9f8w3VhAkT9NpeSkoKw4YN02tZIYRha6wn2dJtRzQWQ2shLM/Q8hGKmtndvq78/97zoyFNqCREY2uUPH/6SElJ4dNPP2XNmjV1LiMnJ4dJkyaRlJSk0wVy0aJFeHh46NU61hDKZihtCh4eHmzfvh0rKytefPFFIiMjsbCwaJK6tBaGfJNgyDdXQoj/kTQ5wpDItUO0dpLnzwDt3LmTiIgIgoODK4x98/f35+TJk01Us9IuqhqNRkny3hj+/PNPnn/+eYqKimjTpg15eXlMnTq1xsBPnvLfP0M+ZoZct8YgEyO0PC31plS+n8KQtKTflmg8ck9pmAym5U8IIYRoSi01kNSHTIhRP+QBU83kGInmqCW1/DVKnj8AR0dHnVx/a9eurXNZZWPcsrOz+fLLL/VaJzk5mY8++giAo0ePMnbsWHr37s3u3bt1llu2bBmjR49m9OjR7Nq1S3l/48aNeHl5YW9vT15enk65Y8aMQaPRMG7cOI4dO1bp9sv2PycnByjtjvnCCy/oLKPRaBg9ejTffPONcpwee+wxRowYgUajYfbs2Tz77LOcPXsWgOLiYvr166eTRmPcuHGkpaWxa9cuvLy8mD59ulL/shlQhRBCVOTas4fyr7VpTfkEy3L5NUQ+v+Z2DBvyWFSluR0jIVqaRuv2WVmuv7rasmULABcvXiQhIYExY8bUuE50dDSRkZEAdO3alSVLlvDpp5/qLHPgwAHOnDnDzp07KSws5KWXXmLo0KGYm5vTv39/hg0bxqRJk3TWGTx4MJ6enqhUKtLT05k1a1aFgBIq3//8/Hx+++03unbtSkZGhvK+u7s77u7uALz88svMnj0bFxcXABYuXMjx48dxdHQkPT2d7t27c+LECTQaDbdv3+bChQs4ODjg5OSEtbW1so/jx49n4sSJjB8/vsZj1ZLU5YLWFDd+rbnFQbR8dfl+S+tAwyj/t7C7fb3KY9uSz0ktbX/uhxwLIVqfJh/zd+jQIcLCwrC0tMTJyYkLFy6wZs0aVq9ejampKdOmTQNg9OjRREVFYWtrq0ygsnz5cjIyMtBoNIwdO5Y9e/YQEhKCo6MjUNpCuGDBAoyNjTEyMlKSvdva2gJUGBv4888/M3DgQNq2bUvbtm1xcHDg0KFDjBw5kt69e1da/7K8gFCaA7Cq3IWVeeaZZ9i1axfTpk0jISGBUaNG1ZiWon///hw8eJAXX3yREydOMGHCBHbs2AHAqVOn6N27d6VpIUxMTLCxseHUqVP06dNH7zo2hobsbtRcLmzNpZ5C1EVdvt8S8DUMff8Wck4SQoiWqdG6fZaleyj7t2vXLgoKCggJCSEqKopNmzZx5cqVWpUZGBiIq6sr8fHxTJkyBV9fX+Li4gA4f/48hYWFODg4cPz4cZycnGosryzYu3PnDnl5eaSkpHD58uUa19u7dy/e3t5Mnz6dsLAwves/YsQIJWfg/v379UotUX7m0BMnTuDq6oqRkRG3bt3ixIkT1aaGcHZ2rrJbalNqTd2NROPLPX1c558QQgghRGvVpN0+z549i62trZLHz8fHh61bt9Z5G97e3kRGRjJ79mxiY2OVfH9XrlxRWv2q8+STT3L69GkmTJiAlZUV/fr1qzK5enleXl54eXlx9OhRVq1axYYNG/Sqr4WFBQ8++CCJiYn07NmT9u3b17iOra0tRUVFXLlyhV9++YUePXrg4uLCqVOnOHHiBC+99FKV61pbW/PLL43Xr18IQ5BVLrmvtGYI0XLp26VVNK36zLEnExUJUXtN3u2zqm6SarWakpIS5XVBQUGNZZmYmODm5sa+fftISkpSJjhp3749N2/e1Ks+M2bMYMaMGUBpy2JlCearMnDgQLKyssjLy9Mr2AQYOXIkoaGhLFmyRO/t9OvXj6+++oqHHnoIlUpFv379OH78OKdOnaJfv35VrldQUICxsbHe2zFkhpxL735V1zolF7baq+13Qm4mhGj+SbCbSz1bo/r827Smv3NLHocrGleTBn89evQgOzubrKws7OzsSExMVD6zsbHhwIEDAKSlpZGdnV1hfTMzM/Lz83Xe8/X1xd/fH1dXVzp06KBsp6axdAB3797lxo0bWFpakp6ezk8//cSQIUOqXefXX3/Fzs4OlUpFWloaRUVFWFpa1ritMsOHDyc3N5cnn3yS3Nxcvdbp378/GzZsYOzYsUBpMLh06VIeeughHnzwwSrXy8zMrLZbaHPSkk98reliZojk+AvRPH8HLfm6IJq32gw5qOq3J99vUV8aLfgrG/NXxt3dnaCgIEJDQ/Hz88PS0pIBAwZw7tw5oHQ8XHx8PBqNBhcXl0pb4Ozt7VGr1fj4+DBu3DimTJmCs7Mz5ubmSpdPKG2RCw8PR6vVolKpOHXqFAEBAdy4cYP9+/ezevVqEhMTKS4u5sUXXwTA3NycZcuW0bZt6SH67LPPiI6O5urVq/j4+PDUU0+xePFivvrqK+Lj42nbti3t27cnIiKiVpO+mJub4+fnV6tj2b9/f5YsWcJjjz0GQKdOnSgpKVFeV+X48eO88cYbtdqWEPVN36eXZcvJBU8IIURz1hwfpoiWy6CSvKekpPDpp5+yZs2aOpeRk5PDpEmTSEpK0pnNc9GiRXh4eODm5lYfVa218hO1NJbyx/PMmTOsX7+eZcuWNWodhBBCCNG8VJcmSR7IidaoJSV5b/Ixf/Vp586dREREEBwcXCGNg7+/PydPnmyimpV2US1Lbt+5c+cG396uXbv46KOPlFlOf//9d958880G364QomVrrJx9LXlcb2O49/jJcRO1Id8XIVquBm/5c3R05NFHH1Vejxo1qtbdHMtMmDCBLVu2kJ2dzYkTJ/RK7p6cnEx6ejoBAQEcPXqUsLAwfvrpJ1asWIG3t7ey3LJlyzh48CAAr7/+OiNHjgTg8OHDLF26lKKiIpycnFi8eDFt27bl5s2bvPPOO1y6dIm7d+/yyiuvVJpAvWz/y4I+Dw8PnJycWL16NQC7d+/mwIEDfPDBB8TFxZGamsr8+fN1yti+fTsxMTEAaLVaZs2axfDhwwkODua7775j3759tGvXjry8PJ577jm+/vprsrKymDlzJllZWZw4cYKffvqJ9evX88EHH9Tp2LcmctMphBCtW0sOnuvyMEYIqL5FuDIt6XcjLX+1UFmKh7rasmULABcvXiQhIUGv4C86OprIyEgAunbtypIlS/j00091ljlw4ABnzpxh586dFBYW8tJLLzF06FBMTU0JDg5mw4YNdO/enVWrVrFjxw58fX3517/+Rc+ePYmKiiIvLw9vb2/GjBlDu3btatz/1NRUzp07R69evWqs/+XLl4mKimLHjh088MAD5Ofnk5eXp3yuVqvZvn07L7zwgs56dnZ2xMfHK+MA7e3tuXz5MpcuXeLhhx+ucbs1qW2+tOZ0gWlJJyvRNGRWNlEVufFuHlry71a+d+Je+s7u25J/F61Jk3X7PHToEGFhYVhaWuLk5MSFCxdYs2YNq1evxtTUlGnTpgEwevRooqKisLW1VcbNLV++nIyMDDQaDWPHjmXPnj2EhITg6OgIlLYQLliwAGNjY4yMjJS0C7a2tgAVuoT+/PPPDBw4kLZt29K2bVsl2fsTTzxBu3bt6N69OwBDhgxhzZo1+Pr6olKpyM/PR6vVkp+fj4WFhTI5TE1eeeUVoqKiWL58eY3LXrt2DTMzM0xNTYHS7qNmZmbK55MnTyYmJob/+7//q7Gsv/71ryQmJvLaa6/pVc/qtOSLh9y4i/sl3xtRlfo8d0peOyFap/r+7cu5o3Vp8ODv3lk+p0+fjqenJyEhIcTExNCtWzdmzZpVqzIDAwN1JoaxsLAgLi6OefPmcf78eQoLC3FwcCA2NlYZ81YdBwcHPvroI6ZOncqdO3dISUnhL3/5C5aWlhQXF3P69GlcXFzYvXs3ly9fBuDFF19kxowZuLu7k5+fT0RERIWgsirPPPMMmzZt4tdff9Wrbh07dsTT05PBgwfj5eWFh4eH8nnXrl3p378/8fHx/PWvf622LGdnZ9atW1cvwV9LJjfuTaOyJ49yQRKianKuEqJ1asjffm27doKci5qbJun2efbsWWxtbZX0DT4+PmzdurXO2/D29iYyMpLZs2cTGxurpHm4cuWKXsnWn3zySU6fPs2ECROwsrKiX79+qNVqVCoVK1asYMmSJRQWFjJkyBDUajUA3377LY6Ojnz22WdkZWUxdepUXF1dMTc3r3F7bdq0Ydq0aaxZs4ahQ4dWu6xarSY6OprTp09z+PBhlixZQlpaGjNnzlSW8ff3Z8aMGQwbNqzasqytrfXOJShK3W8roIwfLKXPcZBAT4jWrbF6Xdz7oEnOPUL8T2u7P9HXiD7OTV2FetNk3T6ryoWnVqspKSlRXhcUFNRYlomJCW5ubuzbt4+kpCRiY2OB0sDz5s2betVnxowZzJgxAyhtWSwLTB977DE2bdoElAZ8mZmZAMTFxeHn54dKpaJbt27Y2tryyy+/0KdPH722Vzbzpz7j/lQqFX369KFPnz64ubkxd+5cneCvW7duODo6kpSUVG05BQUFGBsb61U/Uep+T4JyEi0lx6FUdWNlG+sGtKwOcsNrWFryBCP6aqx9lu9+81PVgwEJ5IWovSYJ/nr06EF2djZZWVnY2dmRmJiofGZjY8OBAwcASEtLIzs7u8L6ZmZm5Ofn67zn6+uLv78/rq6udOjQQdnOF1/UPDvP3bt3uXHjBpaWlqSnp/PTTz8xZMgQoHTMnbW1NYWFhaxbtw5/f3+gtLvl4cOHcXV15erVq5w/f14ZU6gPIyMjJk+ezLp163jiiSeqXC4nJ4erV68q3VfT09MrnbDF39+f6dOnV7vNzMxMvYJNIcT9qWpSD0O4MdGnDpLjq/HJcW0+DCFQr20rqb6TtBnCOaoyVe2jodZXCEPW6GP+3N3dCQoKIjQ0FD8/PywtLRkwYADnzp0DYMSIEcTHx6PRaHBxcVFa4Mqzt7dHrVbj4+PDuHHjmDJlCs7OzpibmytdPgEGDhxIeHg4Wq0WlUrFqVOnCAgI4MaNG+zfv5/Vq1eTmJhIcXExL774IgDm5uYsW7ZMmbwlOjqaAwcOUFJSwsSJExk8eDBQmg7i3XffZcyYMWi1WoKCgvTqYlqer68v//znP3Xe27FjB8nJycrrzZs3Ex4eTm5uLsbGxlhZWbFw4cIKZfXq1YvevXtz5syZKreXkpJSY9dQIcT9a+43JBKIVCQTQYkyjdkltSp2tSy3uZ+ThBD1p8Hz/OkjJSVFZwKXusjJyWHSpEkkJSXpTLyyaNEiPDw8cHNzq4+q1lrZDKVNpWz7ZSksNm3apPespEKI+mUILQZCCCGEqJ26TISjj6a4D2gRUcDOnTuJiIggODi4woyb/v7+nDx5solqVtpFtWx8X+fOnRttu2VJ3q2trQG4dOkSgYGBjR74VfW0XLqVidZIvttCCCGEaEoG0fInmh9JVCwMTW2fykkgJoQQQgh9SMtfPXB0dOTRRx9VXo8aNQo/P786lTVhwgS2bNlCdnY2J06cYMyYMTWuk5ycTHp6OgEBAaxfv55t27ahVquxsrIiLCwMGxsboHQMXtm4vBkzZjB27FgAXnjhBWXSmWvXrtGnTx8iIyPJyMhg7ty5pKWl8dZbbynJ6qva/7IWwZs3b/L+++9z/HhpUNW/f39CQkJ44IEHlHUWLVrEV199xcGDB5UWzqtXrzJv3jx+++03iouLsbGxYd26dUrLX1ZWFidOnOCnn35i/fr1fPDBB3U6xveSgE8YGgnmhBBCiP+pLGCRa6VosuCvsvx/dbVlyxYALl68SEJCgl7BX3R0NJGRkUBpIBYbG4uJiQmbNm1i2bJlrFy5kuvXr/PRRx8RGxuLSqVi3LhxeHh4YGFhoaR/AJg5cyaenp4AdOjQgXnz5rFv375qt3/v/s+bN49evXqxdOlSAD788EPmzZvHhx9+CEBJSQnJycl07dqVo0ePMmjQIGU5Nzc3Jk+eDJTOBgpgZ2dHfHw8jz32GFA6Sc7ly5e5dOlSpbOFCiGEEKLl06cFQwKElkH+jqIyBjfm79ChQ4SFhWFpaYmTkxMXLlxgzZo1rF69GlNTU6UlbfTo0URFRWFra6tMarJ8+XIyMjLQaDSMHTuWPXv2EBISgqOjI1DaQrhgwQKMjY0xMjJSZucsn2qhX79+SnqIb7/9liFDhiipI4YMGcI333zD6NGjleVv3brFkSNHWLJkCVCaSN3a2pqDBw/qvc+//vorqampREREKO+98cYbeHl5KekwUlJS6NWrFyNHjiQxMVEJ/nJzc5W0FAAODg5Vbuevf/0riYmJvPbaa3rXrbmp75w/dWnml5OtEEIIQ3W/1ygZ9tF4mmKWYZnZuOVrsuDv3hQQ06dPx9PTk5CQEGJiYujWrRuzZs2qVZmBgYE6s4ZaWFgQFxfHvHnzOH/+PIWFhTg4OBAbG6vkzbvX9u3bGTp0KFA6g2iXLl2Uzzp37kxOTo7O8snJyQwePBhzc/Na1bW8n3/+GUdHR9RqtfKeWq3G0dGRc+fOYWdnR0JCAqNGjWL48OGsWLGCoqIijIyMePHFF3nrrbfYuHEjbm5ujBs3rsqJZZydnVm3bl2LDv7q+0IkJ77mT59Jh+TvLOqqPseByPdQNAcS8DWepjgnyHmo5TOobp9nz57F1tZWye3n4+PD1q1b67wNb29vIiMjmT17NrGxsUoOwCtXrlSaky8+Pp7U1FQ2btwIQGVz4ahUKp3XCQkJ+Pr61rmOZdu5t9zy7xcWFnLw4EHeffddzM3N6du3L9999x3Dhg3D3d2d5ORkvvnmGw4dOsTYsWNJSEiodP+sra3Jzc29r7oK0dxUdSGrywVOAkZxr5b6PdA331x5EhQIIYThM7hun5UFQVDaElZSUqK8LigoqLEsExMT3Nzc2LdvH0lJScTGxgKlgefNmzd1lv3++++Jiopi48aNtGvXDoAuXbrwww8/KMvk5OTw+OOPK69///13Tp8+zccff6z/DlaiV69enDlzhpKSEmUil5KSEtLT0+nZsyfffPMNt27dwsfHB4A7d+7Qvn17JWF7hw4dGDNmDGPGjGH69OkcPXqUESNGVNhOQUEBxsbG91XX5kzfmxm5gRFVaS43+vXd/Vm0PvKdEUKIlsmggr8ePXqQnZ2tjHNLTExUPrOxseHAgQMApKWlkZ2dXWF9MzMzZQbOMr6+vvj7++Pq6qqM3evRo4cyrg/gzJkzzJ8/n+joaCUvHsCTTz7JihUr+OOPP4DSMYBvv/228vnu3bsZNmzYfQdU3bp1o3fv3kRGRhIQEABAZGQkTk5OdOvWjVWrVrFo0SJlrOHt27fx9PTkzp07/Oc//6Ffv36YmJhw69YtsrKy6Nq1a6XbyczMpFevXvdV1+ZMbmZEayHfddFcSGu6EEI0LoMZ8+fu7k5QUBChoaH4+flhaWnJgAEDOHfuHAAjRowgPj4ejUaDi4uL0jW0PHt7e9RqNT4+PowbN44pU6bg7OyMubm50uUTYODAgYSHhyvdKpcuXcrt27d58803AejatStRUVF06NCB119/neeeew4onYSlLIAE2LVrV4Xxc1euXGH8+PHcunWLNm3aEBMTw65du2ocE7h48WLef/99vLy80Gq19OvXj8WLF3Pnzh2+/fZbQkNDlWVNTU0ZMGAA+/fv59KlS7z//vuo1Wq0Wi2+vr706dOn0m2kpKQorYVCiJarLl32ypPgUTQWCfiEEKJxGXSS95SUFJ0JXOoiJyeHSZMmkZSUpHSphNKceR4eHri5udVHVWutbIbSxtpOYWEhL730Eps2baJtW4Nq8BWiSVQVIEngI4QQQojyJMl7M7Fz504iIiIIDg7WCfwA/P39OXnyZBPVrLSLqkajUZK817eyJO9l3VgvXbpEYGCgBH5C/D8S5AnxPzJOVIjm794ARVrWRWUaPBJwdHTk0UcfVV6PGjUKPz8/vdYdNGiQks8OSvP0bdmyhezsbE6cOFFjMvdnn30Wc3NzJfH5+vXr2bZtG2q1GisrK8LCwpRlp02bxsmTJxkwYIBOS6NWq2XlypXs3r2bNm3aMHHiRCZNmkRKSgqvv/46tra2AHh5eSnj9Srb/7Igz8PDAzMzM6ysrLC2tlaC0vz8fMLDw/n+++8xNjamQ4cOzJ49m759+wKwd+9eAgIC2LVrFz179gQgOzubkSNH0r17d4qKinB2dmbx4sUYGRmRm5tLUVER7du3B+D8+fOcPn1a53gKIYQQ0LqCvabOndaY2xWti6F9r6prLTO0uhqqQ4cOsXjxYkpKSvD19a0yhjp16hTPP/88EREReHt7V1tmgwd/laV0qKstW7YAcPHiRRISEmoM/gCio6OJjIwESgOx2NhYTExM2LRpE8uWLWPlypUAvPrqq9y5c4d///vfOuvHxcXx22+/Kd1Gr127pnzm6upaY5fUyvY/JiYGKysrVqxYwZo1a3jvvfd47733sLW1Zc+ePbRp04YLFy6QkZGhrJOQkMCAAQPYtWsXM2fOVN63s7MjPj6eu3fvMnXqVJKSkvDx8cHV1ZW1a9fi7+8PwLBhw1i1ahWvvfYaJiYmNR63+lbX5nI5OQghhKhPkjtN6KM29y3y962cHJf7c/fuXUJDQ1m/fj2dO3fmueeew8PDg7/85S8VlvvHP/7Bk08+qVe5TdYH8NChQ4SFhWFpaYmTkxMXLlxgzZo1rF69GlNTU6ZNmwbA6NGjiYqKwtbWVhm/tnz5cjIyMtBoNIwdO5Y9e/YQEhKCo6MjUNpCuGDBAoyNjTEyMlJy3j3xxBPK9vv166cz4+fgwYNJSUmpUM/NmzezfPlypYWu/Gyg98vV1ZXPP/+crKwsTp48yT/+8Q9lO4888giPPPIIUNoqePz4cT777DNmzJihE/yVUavV9OnTp0IS+jIqlYrHH3+c/fv3M3LkyHrbB33JCaBuapq4ozU9rRdCCCEai9y3iKZ26tQpunXrpsQDo0aNYt++fRWCv88//5wRI0Zw+vRpvcpt8ODv3lk9p0+fjqenJyEhIcTExNCtWzdmzZpVqzIDAwN1JoKxsLAgLi6OefPmcf78eQoLC3FwcCA2NhYnJ6dKy9i+fTtDhw6tcVsXLlxg165d7N27FysrK9577z1lptH//Oc/+Pj40KlTJ+bMmVPrNAoHDhzg0Ucf5dy5czg6OqJWqytdLjk5GXd3d7p3706HDh1IS0ursF8FBQWcPHmSefPmVbk9Z2dnfvzxxyYJ/kTdSHDX+GTskxBC6Cp/XpRzohD159///rdOr8Pnn3+e559/HiidtLJLly7KZ507d+bUqVM66+fk5JCcnExMTIzhBH+VdXs8e/Ystra2ShDl4+PD1q1b67wNb29vIiMjmT17NrGxsUpahytXriitfuXFx8eTmprKxo0bayy7sLAQY2Nj4uLi2LNnD3PnzmXTpk04OTnx9ddfY2ZmxsGDB3njjTfYs2ePXvWdPHkybdq0wd7enlmzZnH06NFql09MTGTy5MkAjBw5koSEBCX4y8rKQqPR8OuvvzJixAgcHByqLMfa2prc3Fy96mjoJGG7bpcUu9vXW/S+NiY5jg1LbiLvj+TFE01BfqtCNIzywd69KkvIoFKpdF4vXryYoKCgKhuQKtNk3T7vrXwZtVpNSUmJ8rqgoKDGskxMTHBzc2Pfvn0kJSURGxsLlAaeN2/e1Fn2+++/Jyoqio0bN9KuXbsay+7cuTNPP/00UDqpy7vvvgugk7fvqaeeYuHCheTl5VUabN6rbMxfmV69epGenk5JSUmFWUl///13jhw5wrlz51CpVNy9exeVSsXs2bOB/435y83N5eWXX2bfvn14enpWut2CgoL7TkhvKORC1Dpv/Ax58HhVdWvqehmaLNMO//u/BDK1Znf7elNXQQghRCPo0qULly9fVl7n5OTQqVMnnWVSU1N5++23gdKY4eDBg7Rt25bhw4dXWW6TBH89evQgOzubrKws7OzsSExMVD6zsbHhwIEDAKSlpZGdnV1hfTMzM/Lz83Xe8/X1xd/fH1dXVyURe48ePXTG9Z05c4b58+cTHR2t99i94cOHc+TIEZ577jl++OEHpbXyypUrdOzYEZVKxalTpygpKcHS0rIWR+F/7OzscHZ25sMPP+TNN99EpVKRmZnJzz//zNWrV3n22Wd1kry/9NJL/PjjjzpNwZ06dSIoKIi1a9dWGfxlZmbqzLwqRHNmaMGCodWnodxvt9jWcpyqcr/5JcsvV10PCHlAJoQQzZuLiwuZmZlcuHCBzp07k5iYyPLly3WW+frrr5X/BwcHM2zYsGoDP2iCMX/u7u4EBQURGhqKn58flpaWDBgwgHPnzgEwYsQI4uPj0Wg0uLi4KMFWefb29qjVanx8fBg3bhxTpkzB2dkZc3NzpcsnwMCBAwkPD0er1aJSqVi6dCm3b9/mzTffBKBr165ERUUB8MILL/DLL79w+/Zthg4dyuLFi3F3d8fPz4+goCBiYmIwNTVl8eLFAHz11Vds3rwZtVpN+/btWbFiRZWtmfpYvHgxH3zwAV5eXpiYmNChQwfeeecdYmJieO2113SWffrpp/nyyy8rvD98+HBWr17NsWPHcHV1rbCNlJQU5emAEM1Raw8cDIEEFfenPo+f/C2anowRFkI0lLZt2zJ//nxeffVV7t69y/jx4+nVqxebN28GYOLEiXUqV6WtrENpI0tJSdGZwKUucnJymDRpkpKSocyiRYvw8PDAzc2tPqpaa2UzlDaF7Oxs/P39SUhI4OrVqwQGBhITE9MkdWksciEWQjSFps7jZshdostr6uNUk7L6GVq9hDBkrWHYQ11TltWkKY5Rk435q087d+4kIiKC4ODgCmPm/P39OXnyZBPVrLSLqkajUZK8N5Zjx46xcOFCpSvqpUuXCA4ObrTtNyZ9J38pr7ncKAkhmoemPm809fb1ZWj1bKgbOnF/5EFu81LV79rQH/a0VgbR8ieaN5m9Twghak+fh1By8ySEMHTS8ld3TXGMDDr4c3R01JmgZNSoUfj5+dWprAkTJrBlyxays7M5ceIEY8aMqXGd5ORk0tPTCQgIYP369Wzbtg21Wo2VlRVhYWHY2Nhw9uxZFixYwK1bt2jTpg0zZsxQ8ujNnTuX1NRUtFot3bt3Z8mSJZiZmXHz5k3eeecdLl26xN27d3nllVcYP358lftf1mro4eGBmZkZKpWKjh07Eh4ezkMPPYSHhwfbt2/XmUF0165dRERE0KNHD9asWcPGjRsxMTGpdDtCCNGayAMrIWpHfjOitZPgr5E0xHi52owvnDBhApGRkVhZWXHkyBH69u2LiYkJmzZt4ocffmDlypWcP38elUrF//f//X/k5OQwfvx4du3axYMPPsitW7eUlBBLlizB2toaPz8/oqKilAAwLy8Pb29vvv322wqpJ+7d//JB3ooVK7h9+zbvvfdepcHfvft6584dJk6cyM6dO+//IIp6J7m7hBBCiJZDAuaWpSUFf21qXsTwHDp0CG9vbyZOnMiiRYuYPn06AKtXr+aTTz5Rlhs9erSSKuKxxx4DYPny5Rw7dgyNRsOGDRt44YUXOHv2rLLOhAkTSE9P5/z58xgZGSkB1RNPPIGJiQkA/fr1U/JudO/eXZmRtHPnzlhZWZGXlwf8LxegVqvlzz//VLahUqnIz89Hq9WSn5+PhYUFbdvWbvilq6srv/76q97Lm5iYYGNjw6lTp2q1HdE4XHv2UP4JIURTO5bxi/JPCFF7nVz6K/+EMCQGPeHLvWkipk+fjqenJyEhIcTExNCtWzdmzZpVqzIDAwN1Wv4sLCyIi4tj3rx5nD9/nsLCQhwcHIiNjcXJyanSMrZv387QoUMrvH/q1CmKioqws7NT3nv33Xc5ePAgPXv2VCZcefHFF5kxYwbu7u7k5+cTERFRYaKamhw4cKDWOfucnZ05duwYffr0qdV6QgghWhd9H0TVdsItuREWQoimZdDBX/v27YmPj9d57+zZs9ja2iqtbT4+PmzdurXO2/D29iYyMpLZs2cTGxur5Am8cuVKhW6UAPHx8aSmprJx40ad93Nzc3nnnXcIDw/XCeSWLFnC3bt3ef/999m1axfjx4/n22+/xdHRkc8++4ysrCymTp2Kq6ur0lJYncmTJ9OmTRvs7e1rHfhaW1vzyy/yFFeIxiRdf1qHpp6Y5X63r+/sijILoxCtV217AkhvJsNk0MFfVapKpq5WqykpKVFeFxQU1FiWiYkJbm5u7Nu3j6SkJGJjY4HSwPPmzZs6y37//fdERUWxceNGnfF5t27dYvr06cyaNYt+/fpVWq+RI0fyySefMH78eOLi4vDz80OlUtGtWzdsbW355Zdf9GqRi4mJqTQo1UdBQQHGxsZ1WlcIUTdyc9w6NPVNzv1uX9/vqXyfRWtU1cOVpn7o09jsbl9X/i/nguar2QV/PXr0IDs7m6ysLOzs7EhMTFQ+s7Gx4cCBAwCkpaUp4/3KMzMzIz8/X+c9X19f/P39cXV1pUOHDsp2vvjiC2WZM2fOMH/+fKKjo7G2tlbeLyws5I033kCj0fDMM88o72u1WrKysujWrRtarZb9+/fTo0fpSaFr164cPnwYV1dXrl69yvnz57G1tb3vY1OTzMxM+vdveT/WltCy0tLzDraEv5EQLVl13Teby29WWiVFQ6nqOmxo12d9W+bsbl+v0+9DflMtg0EHf/eO+XN3dycoKIjQ0FD8/PywtLRkwIABnDt3DoARI0YQHx+PRqPBxcVF6Rpanr29PWq1Gh8fH8aNG8eUKVNwdnbG3Nxc6fIJMHDgQMLDw9FqtahUKpYuXcrt27d58803gdIALioqiqSkJI4dO8b169fZsWMHAB988AH29vbMmTNHmdjF3t6ehQsXAvD666/z7rvvMmbMGLRaLUFBQXVuzSvj4+OjdDd95plnePfddyssc/z4cd54441qy2moi2dDPh1rCScjQ7uA1LeW8DcSLV9rfkjREva3JeyDEPejpd9LiPph0Kke9FGb1A1VycnJYdKkSSQlJemM11u0aBEeHh64ubnVR1Vr7X5TXZQ/NmfOnGH9+vUsW7asHmtoeOojeG0NyUqFEM1fS+sx0BxT3khrY+umb0uboX2fW1t31frQklI9GHTLX2PYuXMnERERBAcHV5hx09/fn5MnTzZRzUq7qGo0GiXJe23s2rWLjz76SJmx9Pfff1daLVuy+rjwykmw/rXmFpXmeEMrmof7/T4Z2u+yufw+dH7TBnDcWrO63pDX13etuXxn79Vc6y3qR5MFf46OjjqpCkaNGoWfn1+tyxk0aBAREREAZGdnc+LECcaMGVPjesnJyaSnpxMQEMDvv//O6tWrlYTuYWFh2NjYUFBQwMcff8yHH35IcXExL730EhMnTgRg7ty5pKamotVq6d69O0uWLMHMzAytVsvixYs5ePAg7du354MPPqg0ZUTZ/pcFdh4eHpiZmaFSqejYsSPh4eHs3r2bZ599ljt37gBQVFTEuHHjWLRoEX379lXKKC4uRq1WM3bsWGU20E6dOgEoOQwLCwuJi4vjb3/7W62PsRD3K8u0g/L/Tk1XjSYhF1lhqAwh4LtfTRHAym+6aTVki3dDPaxr6iBViPKarNvn/XZprExtuoBOmDBBCfaOHDlC3759MTExYdOmTfzwww+sXLmSwsJCANq1a0d+fj5jxoxh8+bNdO7cmVu3bimpGZYsWYK1tTV+fn4cPHiQzz//nHXr1nHy5EkWL17Mtm3batx/Dw8Ptm/fjpWVFStWrOD27du899577Nq1i+3btyv7dfHiRUJDQyuUce3aNQIDA+nfv78S4GVnZ+Pv709CQgJarZaxY8eyefNmJVl9Q6hq0oCWcJMhhNBf+Zuduk4uUFO5tSE3UUIIIepKun02oEOHDhEWFoalpSVOTk5cuHCBNWvWsHr1akxNTZk2bRoAo0ePJioqCltbWyUIWr58ORkZGWg0GsaOHcuePXsICQnB0dERKA34FixYgLGxMUZGRsokK0888YSy/X79+imzfJZP51BYWKiTRqIs8NNqtfz555/K+/v27ePZZ59FpVLRr18/bty4QW5urtISpw9XV1c+//xzAEaOHElsbCzr1q1jy5YtyqQy97K2tub999/nueeeY+bMmRXSYahUKh5//HH279/PyJEj9a5LbTVUkCf904WoXm0vTPUZkFWmqt/o/Y6Rkt++EPppaWNCRfNX2XdSvouNr8mCv3tn8pw+fTqenp6EhIQQExNDt27dap3EPDAwUKflz8LCgri4OObNm8f58+cpLCzEwcGB2NjYSrtiAmzfvp2hQ4cqr3/77Tf8/PzIyspi9uzZOmPv3n33XQ4ePEjPnj0JDg4GSieP6dKli7JMly5dyMnJqVXwd+DAAZ0usXPnzmXkyJG8//77SiqKyjzyyCOUlJRw7do1OnbsWOFzZ2dnfvzxxwYN/hqKnByaTl1v1qvqPiNj4BpGczmWhtwLQL6boiWR77AwNPKdNAxNFvy1b9+e+Ph4nffOnj2Lra2tkqLBx8eHrVu31nkb3t7eREZGMnv2bGJjY5VUDleuXKk0tUJ8fDypqals3LhRea9r1658+eWX5OTk8MYbbzBixAglsFqyZAl3797l/fffZ9euXYwfP57KetFWlZT+XmXj9ezt7XUC32+++YaHHnqI//73vzWWUV0vXmtra3Jzc/WqizBMTTG+pa7baS55kUTtNNfZ7arSlAFfXVpmDG2SFtE4pPeLEKK+GFy3z6oCJbVardPtsqCgoMayTExMcHNzY9++fSQlJREbGwuUBp43b97UWfb7778nKiqKjRs36nT3LNO5c2d69erFsWPH8Pb21qnXyJEj+eSTTxg/fjxdunTh8uXLyueXL1/Wu9UvJiamQlCak5PD559/zvbt25k0aRLp6ek4ODhUuv6FCxdQq9U6SejLKygowNjYWK+6CMMkN3uiqRnaTef9pmZpyv2py7blHNA6GdrvTgjRfBlU8NejRw+ys7PJysrCzs6OxMRE5TMbGxsOHDgAQFpaGtnZ2RXWNzMzIz8/X+c9X19f/P39cXV1VbpM9ujRQxnXB3DmzBnmz59PdHS0TuB0+fJlOnToQPv27fnjjz84fvw4U6ZMQavVkpWVRbdu3dBqtezfv58ePUpPzB4eHmzcuJFRo0Zx8uRJHnjggVp1+bzXkiVL8Pf3p0uXLgQHBxMaGsq//vWvCkFyXl4ef//733nxxRerDKAzMzN1upMKIVomfVrnWsrNZFPvR1WTXJUnAVvrIV2HRWsnuS8Nn8GM+XN3dycoKIjQ0FD8/PywtLRkwIABnDt3DoARI0YQHx+PRqPBxcVF6Rpanr29PWq1Gh8fH8aNG8eUKVNwdnbG3Nxc6fIJMHDgQMLDw9FqtahUKpYuXcrt27eVPHhdu3YlKiqKjIwMPvjgA1QqFVqtlldeeQV7e3tKSkqYM2cO+fn5aLVa7O3tWbhwIQBPPfUUBw8exMvLCxMTE8LCwup8jL777jt+++03nnvuOaA0sNy6dSs7d+5k7NixyjEsS/Wg0WiYOnVqleWlpKTw9ttv17k+dVHbSSjkYtm6yI1Sw5Bj2XjkxqZy99si21y19P0Tjas5dvNuLvVszZos1YM+apO6oSo5OTlMmjSJpKQknSTuixYtwsPDAzc3t/qoaq01RKqLe5VP9XD16lUCAwOJiYlp0G0KIURdyJgmIYQQhkpSPTQTO3fuJCIiguDgYJ3AD8Df35+TJ082Uc1Ku6hqNBolyXt9O3bsGAsXLsTS0hKAS5cuKTOStjT6Phlrjk/QhGgtJNgThqDsBk++j0KIlqrRW/4cHR11xp2NGjUKPz+/OpU1YcIEtmzZQnZ2NidOnGDMmDE1rpOcnEx6ejoBAQGsX7+ebdu2oVarsbKyIiwsDBsbG2XZW7du8cwzz+Dl5cX8+fOB0nQSqampGBkZ4eLiQmhoKEZGRiQnJ7Nq1SratGmDWq1m7ty5uLq6Vrn/ZUGfh4cHZmZmQGlqivDwcKUO5VsHAwMDGTBgAC+88AIAJ0+e5L333mPHjh08/fTTmJmZoVKp6NixI+Hh4Tz00EO8/PLLpKam8tlnn2Fvb8/UqVOJiYmhbduWG/NL64EQQgghhKhPLanlr9GDv4bo7lib7qETJkwgMjISKysrjhw5Qt++fTExMWHTpk388MMPrFy5Ull20aJF/P7771hYWCjB38GDB5U8gIGBgbi6uvLCCy+Qn5+PqakpKpWK9PR0Zs2axe7duyts/9799/DwYPv27VhZWfHhhx+Sm5vLokWLKix79epVnn/+ebZt20aHDh3w9fXl3XffxdXVVaeMFStWcPv2bd577z0AXn75ZWbPno2LiwsfffQRdnZ2+Pj41O1Ai1bDEJID1zSRhrTeCiFE45Dx2aK1a0nBn8E0AR06dIiwsDAsLS1xcnLiwoULrFmzhtWrV2Nqasq0adMAGD16NFFRUdja2irB0fLly8nIyECj0TB27Fj27NlDSEgIjo6OQGnAt2DBAoyNjTEyMlLSKTzxxBPK9vv166czA2hqairXrl3D3d2d1NRU5f2nnnpK+X+fPn3IyckBUFrvAO7cuaN3br/y+vXrx+eff17pZx07duSVV15h2bJlODs7Y29vX2nLoqura5VlDB8+nOXLl0vwJ4Dancia4uQkwZ0QQhgGCfiEaDkaPfi7d5bP6dOn4+npSUhICDExMXTr1k0nwbk+AgMDdVr+LCwsiIuLY968eZw/f57CwkIcHByIjY3Fycmp0jK2b9+utOiVlJQQHh7O0qVLOXz4cKXLFxUVER8fz7x585T39u7dy/Lly8nLy6vTJDXffPMNw4cPr/LziRMn8vzzz5OSkqLkLLzXgQMHqkzn0KtXL06fPl3reomWSS7mQhiOujxVlt+wEKI5qew8J+exxtfowV/79u2Jj4/Xee/s2bPY2toq6Rt8fHzYunVrnbfh7e1NZGQks2fPJjY2VknzcOXKlQpJ1AHi4+NJTU1l48aNAGzatImhQ4fStWvXKrexcOFCXF1ddVrfvLy88PLy4ujRo6xatYoNGzboVd/Jkydz9epVrK2tqw1827Rpw/PPP09qaqoykUv5Mtq0aYO9vX2VZajVaoyMjLh16xbm5uZ61U0IIUTDa643QDLOWgihLzk/GAaD6fZZVTdJtVpNSUmJ8rqgoKDGskxMTHBzc2Pfvn0kJSUprWTt27fn5s2bOst+//33REVFsXHjRtq1awfAiRMn+PHHH9m8eTP5+fkUFRVhampKUFAQAB999BF5eXl89NFHlW5/4MCBZGVlkZeXV2mwea+YmBhMTU0JDg7mww8/5N13361y2TZt2lSYubSsDH22VVhYiLGxcY3LNScyi2fzVV1rh93t6/L3bMb0SX4O8ptt7lrLzVxzGfMmCbaFEDUxiOCvR48eZGdnk5WVhZ2dHYmJicpnNjY2HDhwAIC0tDSys7MrrG9mZkZ+fr7Oe76+vvj7++Pq6kqHDh2U7ZQf13fmzBnmz59PdHQ01tbWyvvLly9X/h8XF0dqaqoS+G3bto1vv/2WDRs26ARhv/76K3Z2dqhUKtLS0igqKqrQOled9u3bM3fuXMaMGcOMGTOUOten33//HSsrK4yMjOq97KYkF7fmy5Bvolqq+x20ru/frLn/LvWd9Eif1ACGGjhUF6A3979ffTOkv1t17ufv1hy/DxLsClF7TT7mz93dnaCgIEJDQ/Hz88PS0pIBAwZw7tw5AEaMGEF8fDwajQYXFxela2h59vb2qNVqfHx8GDduHFOmTMHZ2Rlzc3OlyyeUtsiFh4ej1WpRqVQsXbqU27dv8+abbwLQtWtXoqKiqq3/3//+dx5++GGef/55oLSrZ0BAAF999RXx8fG0bduW9u3bExERUetJXzp16sTo0aP517/+xRtvvMGdO3eUcYgAU6dOxcLColZllpeSkqIzYU190edmsrlcOA2BtGSKhlT2W5TuetXT93jos5yhHltDOL/UZ2As58770xyPWXOsc32o6r7LUM81wrA0eqoHfdQmdUNVcnJymDRpEklJSTotdIsWLcLDwwM3N7f6qGqtNUSqi+qUT/UQEBDA22+/TY8ecnIQ9a+mhwByURJCCCFEcySpHgzczp07iYiIIDg4uML4OH9/f06ePNlENSvtoqrRaJQk7w3p5Zdf5sKFCxgZGVFYWMjw4cMl8BMNRoI70Vw0x+5tQgghRH0wyJY/IYQQQghROX0eYEg3WCHqj7T81YKjo6NO3rlRo0bh5+dXp7ImTJjAli1byM7O5sSJE4wZM6bGdZKTk0lPTycgIID169ezbds21Go1VlZWhIWFYWNjU6Ge5cf+zZ07l9TUVLRaLd27d2fJkiWYmZmh1WpZvHgxBw8epH379nzwwQeV5hAsK7espW/79u3ExMQAoNVqmTVrFsOHDyc4OJgffvgBc3NzCgoK6Nu3L4GBgUrroIeHh5JI3sLCgvDwcKXulXUl3bBhAxs2bMDDw4P58+cTHh7O0KFDGTx4cF0OvRBCCCEMhD7BnAR8oiHJw4Xmq8GDv8ry+tXVli1bALh48SIJCQl6BX/R0dFERkYCpYFYbGwsJiYmbNq0iWXLlrFy5cpq6zl37lwlJ96SJUv417/+hZ+fH4cOHSIzM5M9e/Zw8uRJFixYwLZt2yqsX77cy5cvExUVxY4dO3jggQfIz88nLy9PWXb27Nl4e3uj1WqJiYlh0qRJfPnll0oKirJ0Dh9++CH//Oc/WbRoUZX7PWXKFB588EFSU1MBeOmllwgJCWmy4E/fySXqexIKmdRCCCGEEKJ+ScDXfFVMGNdIDh06hLe3NxMnTmTRokVMnz4dgNWrV/PJJ58oy40ePVpJ7/DYY48BpakYjh07hkajYcOGDbzwwgucPXtWWWfChAmkp6dz/vx5jIyMlPx3TzzxBCYmJgD069ePy5cv11jPssBPq9Xy559/Ku/v27ePZ599FpVKRb9+/bhx4wa5ubnVlnXt2jXMzMwwNTUFSsf/PfLIIxWWU6lUTJkyhY4dO3Lo0KEKn/fr14+cnJwa616ejY0N169f58qVK7Var7649uyh8+9+l6vv7VYl9/Rx5Z8QwvAcy/hF+SeEEEKI6jV4y9+9qR2mT5+Op6cnISEhxMTE0K1bN2bNmlWrMgMDA3VmA7WwsCAuLo558+Zx/vx5CgsLcXBwIDY2ttKumADbt2/XSaNQUFDAuHHjaNu2LX5+fgwfPlz57N133+XgwYP07NmT4OBgoHQ20S5duijLdOnShZycHDp16lRlvR0cHOjYsSOenp4MHjwYLy8vPDw8qly+d+/e/PJLxRuab775Rqd++urduzfHjx9nxIgRtV63tZInWw1L3xt2abFtmeoSsN37XajP70Z91KeuDDlfmXTvEkKIlqNJun2ePXsWW1tbJWefj48PW7durfM2vL29iYyMZPbs2cTGxiq5/a5cuaK0+pUXHx9PamoqGzduVN7bv38/nTt35sKFC0yePJlHH30UOzs7oLS75927d3n//ffZtWsX48ePp7J5cmrK66dWq4mOjub06dMcPnyYJUuWkJaWxsyZMytd/t5tTJ48matXr2JtbV3rgBnA2tq6xtZJIRqTBHUtl76BlN3t6wYTUDTl99FQjkFlDLluQgghaqfJUj1UFSip1WpKSkqU1wUFBTWWZWJigpubG/v27SMpKYnY2FigNPC8efOmzrLff/89UVFRbNy4URlLBygTqzzyyCM8/vjjnDlzRgn+yuo1cuRIPvnkE8aPH0+XLl10uo1evny52la/8vvdp08f+vTpg5ubG3Pnzq0y+Dt79qzOGL2YmBhMTU0JDg7mww8/5N13361xe+UVFBTQvn37Wq0jmrfadFeVGzxRnySwF0IIIQxPkwR/PXr0IDs7m6ysLOzs7EhMTFQ+s7Gx4cCBAwCkpaUp4/3KMzMzIz8/X+c9X19f/P39cXV1pUOHDsp2vvjiC2WZM2fOMH/+fKKjo7G2tlbe/+OPPzAxMaFdu3bk5eVx/PhxXn31VbRaLVlZWXTr1g2tVsv+/fuVPHkeHh5s3LiRUaNGcfLkSR544IEag7+cnByuXr2qdEVNT0/n4YcfrrCcVqvl888/58qVK7i7u+t81r59e+bOncuYMWOYMWOGsq/6yMzMxNvbW+/l65NMvNI0JKATQhiS+70WGMK1pHwd5FomhGhuGn3Mn7u7O0FBQYSGhuLn54elpSUDBgzg3LlzAIwYMYL4+Hg0Gg0uLi5K19Dy7O3tUavV+Pj4MG7cOKZMmYKzszPm5uZKl0+AgQMHEh4ejlarRaVSsXTpUm7fvs2bb74J/C+lQ0ZGBn//+99RqVRotVpee+01/vKXv1BSUsKcOXPIz89Hq9Vib2/PwoULAXjqqac4ePAgXl5emJiYEBYWVuOxKC4uJjw8nNzcXIyNjbGyslLKA1i6dCmRkZH8+eef9O3bl88++0yndbJMp06dGD16NP/617944403uHPnjs74xalTpzJ16lSddYqKivj1119xdnausZ4NQS6QwpBVN6ZJEoILUX/u91pQ39cSfXtHlP+tG9r1TILRuqvuYYIcV9FSGUSS95SUFJ0JXOoiJyeHSZMmkZSURJs2/5vEdNGiRXh4eODm5lYfVa21ynLwNZa4uDhSU1OZP38+e/fuJS0trU5jBYUQQgiQhyF1VdfZaCXoEMIwSJJ3A7Nz504iIiIIDg7WCfwA/P39OXnyZBPVrLSLqkajUZK8N5YNGzawefNmZWbP4uJiXnnllUbbvhBCiJZHAry6aUlBnLSICdG8NVmev/IGDRrEoUOH0Gg0yr+1a9fqvf6zzz7LwYMHeeaZZ4DSPH8A2dnZHD58GE9PzxrLSE5O5qOPPgJg/fr1jBw5kjFjxjB58mQuXryoLHfp0iVeeeUVnnnmGUaOHKmMSdy4cSNeXl7Y29vrJG5fsGABJSUl+Pn5MW7cOI4dO1bp9h0dHdFoNEr+vu3btzNmzBjGjBnD6NGjSU5OBiA4OBh3d3cKCwsByMvLU9JFZGdnM3r0aACcnZ1Rq9V8/fXXQOlYwQ0bNuhxNIUQQojWrXyO13tbO6v7rDWoz1y8QojGZzAtf5WlhKirLVu2AHDx4kUSEhIYM2ZMjetER0cTGRkJlAZisbGxmJiYsGnTJpYtW8bKlSsBmDNnDv7+/gwZMoT8/HylpbF///4MGzaMSZMm6ZQ7ePBgPD09UalUpKenM2vWLHbv3l1h++X3//Lly0RFRbFjxw4eeOAB8vPzdQJKtVrN9u3beeGFF6rcH1dXV9auXYu/vz8Aw4YNY9WqVbz22mtKonshROtlyHnlGkJtu+zIjW3rVt3voaX/VoQQLZvBBH9VOXToEGFhYVhaWuLk5MSFCxdYs2YNq1evxtTUlGnTpgEwevRooqKisLW1VcbZLV++nIyMDDQaDWPHjmXPnj2EhITg6OgIlLYQLliwAGNjY4yMjJScgE888YSy/X79+ikzhv78888UFxczZMgQoLRLZ5nevXtXWv/yy9y5c6fGXIAA165dw8zMDFNTU6WM8uVMnjyZmJgY/u///q/mA/j/qFQqHn/8cfbv38/IkSP1Xk8I0TK1thtYCeaEqLuqHp7I70qI5sdggr97ZwWdPn06np6ehISEEBMTQ7du3Wo9WUlgYKDORDIWFhbExcUxb948zp8/T2FhIQ4ODsTGxirpF+61fft2ZSbNzMxMHnzwQQICAsjOzmbw4MEEBQWhVqurrcfevXtZvnw5eXl5ek1q4+DgQMeOHfH09GTw4MF4eXkpXTuhdJbS/v37Ex8fz1//+ld9DwfOzs78+OOPEvwJYeCqm31UND/63Dg3VgoDGa/VeFrS5DjyXRGi5TCY4K+ybp9nz57F1tZWSffg4+PD1q1b67wNb29vIiMjmT17NrGxsUpaiCtXriitfuXFx8eTmprKxo0bgdJJU44dO8bOnTvp2rUrb731FnFxcfj6+la7XS8vL7y8vDh69CirVq2qceydWq0mOjqa06dPc/jwYZYsWUJaWppOMnh/f39mzJjBsGHD9N5/a2trcnNz9V5eCNFwqut22dxuDBtTXabmb2p1uXHWp5tqXcqVm/jGY0jfwZZEHmAYHmkZbl4MJvirSlXdJNVqNSUlJcrrgoKCGssyMTHBzc2Nffv2kZSURGxsLFAaeN68eVNn2e+//56oqCg2btyo5Nrr0qULvXv35pFHHgHA09OzVjOJDhw4kKysLPLy8ioNNstTqVT06dOHPn364Obmxty5c3WCv27duuHo6EhSUpLe2y8oKMDY2Fjv5YUQDUduDOumpR43uUkSQj8N+VvRd2yw/F51VdWLoaEeYon7Y9DBX48ePcjOziYrKws7OzsSExOVz2xsbDhw4AAAaWlpyqyb5ZmZmZGfn6/znq+vL/7+/ri6utKhQwdlO2Xj+gDOnDnD/PnziY6OxtraWnnfxcWFP/74QwneUlJSakya/uuvv2JnZ4dKpSItLY2ioiIsLS2rXScnJ4erV68qXVHT09N5+OGHKyzn7+/P9OnTqy2rvMzMTB599FG9lxfNh1ywGk5zecrc3J+8GvoENFV1xS1739DqK1qPxuoy3NzU5dwtx+7+yTE0fAYT/N075s/d3Z2goCBCQ0Px8/PD0tKSAQMGcO7cOQBGjBhBfHw8Go0GFxcXpWtoefb29qjVanx8fBg3bhxTpkzB2dkZc3NzpcsnlLbIhYeHo9VqUalULF26lNu3b/Pmm28CpWPsoqKiUKvVzJkzh8mTJwPg5OSkdPn87LPPiI6O5urVq/j4+PDUU0+xePFivvrqK+Lj42nbti3t27cnIiKixklfiouLCQ8PJzc3F2NjY6ysrFi4cGGF5Xr16kXv3r05c+aMXsc4JSWFt99+W69lW5vmPsZKTrYNp7kc2+ZSz6oY+u+uqvoZer1Fy9fcf/sNRY6LEJVTabVabVNXQl8pKSk6E7jURU5ODpMmTSIpKUknIfyiRYvw8PDAzc2tPqpaa2UzlNan7Oxs/P39SUhI4OrVqwQGBhITE1Ov2xBCCFH/ylot7r2BbS4t0XVhSPtWXW+Kpq6bEKLx1TZdkL5qOp8cOnSIxYsXU1JSgq+vL35+fjqff/HFF6xbtw4o7fG4YMECHBwcqi3TYFr+GsPOnTuJiIggODhYJ/CD0i6UtRm/V9/MzMyU5PadO3e+7/KOHTvGwoULlS6mly5dIjg4+L7LrXU9/t+Pxe72dXlCLloU6WolGlJV36em/p7VdAN0P/Vr6n0rz5DqIoRone7evUtoaCjr16+nc+fOPPfcc3h4ePCXv/xFWcbW1paNGzdiYWHBwYMHCQkJYdu2bdWW26xa/oQQQjSu6sbitaSp7IUQQlSvuQ+RuR9N0fJ34sQJPvroIz755BMApedjVfN9/PHHH4wePZpvvvmm2m02aMufo6OjzgQjo0aNqtBcqa8JEyawZcsWsrOzOXHiBGPGjKlxneTkZNLT0wkICGD9+vVs27YNtVqNlZUVYWFh2NjYAKWtYu+99x6//fYbKpWKtWvXYmtry+HDh1m6dClFRUU4OTmxePFi2rYtPWQpKSmEhYVRXFyMpaWlkg6isv0va83bvn270u1Sq9Uya9Yshg8fzssvv8zs2bNxcXEBdLtrpqSkMGnSJP75z38quf6mT5/OK6+8wqBBg3j55ZfJzc2lffv2QOksoB9++CEbNmxgw4YNeHh4MH/+fMLDwxk6dCiDBw+u0/GHun/x5QmqEM1XdRf41nbxF0KI1kzO+Y0rJyeHafradAAAUXZJREFULl26KK87d+7MqVOnqly+fG7y6jRo8FdZ7r662rJlCwAXL14kISFBr+AvOjqayMhIoDQQi42NxcTEhE2bNrFs2TJWrlwJwJw5c/D392fIkCHk5+fTpk0bSkpKCA4OZsOGDXTv3p1Vq1axY8cOfH19uXHjBgsXLiQ6OpqHH36Ya9eu1bj/ly9fJioqih07dvDAAw+Qn59PXl6eXvvepUsXoqKidBK9l/ePf/xDCRzLTJkyhQcffJDU1FQAXnrpJUJCQu4r+GvtQZx08xNCCCGEEPXl3//+N//+97+V188//zzPP/88UNpQdK+qJo08cuQI27dvZ9OmTTVus0nG/B06dIiwsDAsLS1xcnLiwoULrFmzhtWrV2Nqasq0adMAGD16NFFRUdja2ioToixfvpyMjAw0Gg1jx45lz549hISE4OjoCJS2EC5YsABjY2OMjIyUfHpPPPGEsv1+/fopqR1+/vlniouLGTJkCFA69g4gLy+Pdu3a0b17dwCGDBnCmjVr8PX15csvv8TLy0tJv1A+HURVrl27hpmZGaampsp2yrZVEwcHB4qLi/nuu++UetaWjY0N169f58qVKzz00EN1KqM+NceuAxLsCSH0VVWX2OZyvhOiPH0m46nPCXuaKvWLIU06ZIga+3vQGpQP9u7VpUsXLl++rLzOycmhU6dOFZZLT0/nvffeY926dTWmk4MGDv7uTd8wffp0PD09CQkJISYmhm7dujFr1qxalRkYGKgz46eFhQVxcXHMmzeP8+fPU1hYiIODA7GxsUqevHuVbxbNzMzkwQcfJCAggOzsbAYPHkxQUBCWlpYUFxdz+vRpXFxc2L17t/IHyMzMpLi4mJdffpn8/HwmTZrEs88+W229HRwc6NixI56engwePBgvL68qW/IqM2PGDFauXFlp8BcUFKR0+3Rzc2POnDmVltG7d2+OHz/OiBEj9N5uQ5EbICFESybnuKbVUoYp1DZ/Z0M9dNDnuNTnsWuq34+h/f0NTWN/D1o7FxcXMjMzuXDhAp07dyYxMZHly5frLHPp0iVmzpzJ0qVLlQarmjR6t8+zZ89ia2ur5OXz8fFh69atdd6Gt7c3kZGRzJ49m9jYWCV/35UrV5RWv/Li4+NJTU1VxugVFxdz7Ngxdu7cSdeuXXnrrbeIi4vD19eXFStWsGTJEgoLCxkyZAhqtRoonX0nLS2NDRs28OeffzJhwgT69u1b7UFXq9VER0dz+vRpDh8+zJIlS0hLS2PmzJmVLn9vs66rqytQOovnvSrr9lkZa2trcnNza1xOiPL0vYmSGV2FEIaipdyA1nY/9DkHS8uMEM1D27ZtmT9/Pq+++ip3795l/Pjx9OrVi82bNwMwceJEPv74Y65fv67kA1er1cTFxVVfboPXvBJV9VdVq9WUlJQorwsKCmosy8TEBDc3N/bt20dSUhKxsbFAaeB58+ZNnWW///57oqKi2LhxI+3atQNKm1R79+7NI488AoCnp6eS8uGxxx5T+s5+++23ZGZmKutYWlpiamqKqakprq6upKen1xhxq1Qq+vTpQ58+fXBzc2Pu3LnMnDkTS0tLbty4oSz3xx9/0KFDhwrr+/v7889//lOZdKa2CgoKlBbCxiazAjZfcnMghBAth5zThWg+nnrqKZ566imd9yZOnKj8f/HixSxevLhWZbapeZH61aNHD7Kzs8nKygIgMTFR+czGxoYzZ84AkJaWRnZ2doX1zczMyM/P13nP19eXRYsW4eLiogRNPXr04Ndff1WWOXPmDPPnz+ef//ynzhg9FxcX/vjjD2XylZSUFCV/RtlELoWFhaxbt44JEyYApQHisWPHKC4u5s6dO5w6dYqePXtWu985OTmkpaUpr9PT05Uxg48//jhffPGFMrBzx44dDBo0qEIZTz75JDdu3CA9Pb3abVUlMzOTXr161Wnde+WePq7800cnl/5V/hNCCCGE4artNV9U71jGL8o/IRpbo475c3d3JygoiNDQUPz8/LC0tGTAgAGcO3cOgBEjRhAfH49Go8HFxUXpGlqevb09arUaHx8fxo0bx5QpU3B2dsbc3Fzp8gkwcOBAwsPD0Wq1qFQqli5dyu3bt3nzzTcB6Nq1K1FRUajVaubMmcPkyZMBcHJywtfXFyidLfTAgQOUlJQwceJEZabMnj174u7ujo+PD23atOG5557TSWlRmeLiYsLDw8nNzcXY2BgrKyulifb//u//+OWXX/Dx8UGlUuHs7ExgYGCl5fj7+/P666/rvFd+zJ+lpSUbNmyosF5RURG//vorzs7O1dZTXxK0tV7SZUgIw9NcZiNuLvVsae53krXWeM2vS6Cr73GS771oSk2e5D0lJUVnApe6yMnJYdKkSSQlJdGmzf8aMxctWoSHhwdubm71UdVaK5uhtKnExcWRmprK/Pnz2bt3L2lpabWeYEcYFgm8hBCi9mrTS0WI5kTf1kO5Z7g/TZHkvaE0yZi/+rRz504iIiIIDg7WCfygtJWsbPxeUzAzM0Oj0ShJ3hvThg0b2Lx5szKzZ3FxMa+88kqj1kHUPzl5i9pqqinThTAk9/u9l+BRGKrGvC+o7eyzwjA1afDn6OiodJfUaDSMGjUKPz+/WpXx7LPP8uyzzzJhwgSeeeYZsrOzOXHiBGPGjFFSK1QlOTmZ9PR0AgICWL9+Pdu2bUOtVmNlZUVYWBg2NjYcOXKEJUuWKOv88ssvREREMHz4cA4fPszSpUspKSnB1NSUDz74gG7dupGcnMyqVauwtrZGrVYrU7RWtf9r164lICCAwsJC/vjjD/78809l+Y8//hhLS0uWLl3Kd999h7m5OW3atGHChAlcu3aN3bt3A/Df//5XOZbjx48HSid4uXXrFgCnTp2iQ4cO95XkXbRO1T3tkhO+4ZObUSHun/yOhJBrfkvRpN0+G6JbZG26kU6YMIHIyEisrKw4cuQIffv2xcTEhE2bNvHDDz+wcuVKneWvX7/O008/zcGDBzExMWHEiBFERkbSs2dP/vWvf3H69Gk++OAD8vPzMTU1RaVSkZ6ezqxZs5QgrbzK9r98V80yb731Fo888gizZs2iTZs25OXlsX37dp1AuaayLl68SEhICJ9++qk+h1EIIYRoteo6sYkEiUK0TNLts4EdOnSIsLAwLC0tcXJy4sKFC6xZs4bVq1djamrKtGnTABg9ejRRUVHY2toqwc/y5cvJyMhAo9EwduxY9uzZQ0hICI6OjkBpwLdgwQKMjY0xMjJScgE+8cQTyvb79evHF198UaFeX331Fe7u7piYmCjvlbWs3bp1i06dOgGl3T3L3Llzp8rUFvrIysri1KlTLF++XOnWamVlVesWUhsbG65fv86VK1d46KGH6lwfUTMZlydaMvl+i9ZAgjghREvVpMHfvbOBTp8+HU9PT0JCQoiJiaFbt261nqAkMDBQp+XPwsKCuLg45s2bx/nz5yksLMTBwYHY2FicnJwqLWP79u0MHTq0wvuJiYlMnTpVeb148WL8/PwwNjbG3NxcJ1n93r17Wb58OXl5efc1mc25c+dwcHCoMJ6xLnr37s3x48eVcYCiYTTWDXFdnkLJzbq4Xy3tOyRjuYSof4Y21lgmRRHif5o0+Gvfvj3x8fE67509exZbW1slzYOPj49OUFVb3t7eREZGMnv2bGJjY5V0EFeuXFFa/cqLj48nNTWVjRs36ryfm5vLf//7X5588knlvQ0bNrB27Vr69u1LdHQ0S5YsURItenl54eXlxdGjR1m1alWl6Rfq4p///Ce7d+/m2rVrfPvtt7Va19ramtzc3Hqph2h6cpESTc3QbvCqU+XNn2kHnZfyuxLi/hnauUB+10L8j0F2+6yqm6RaraakpER5XVBQUGNZJiYmuLm5sW/fPpKSkoiNjQVKA8+bN2/qLPv9998TFRXFxo0badeunc5nSUlJeHl5YWRkBEBeXh7p6en07dsXgJEjR/Lqq69W2P7AgQPJysoiLy+v0mCzJn/5y19IT0+npKSENm3aMGPGDGbMmMFjjz1W67IKCgqUfIBCCHG/GusGrz7ybcnNnxBCCGGAwV+PHj3Izs4mKysLOzs7EhMTlc9sbGw4cOAAAGlpaWRnZ1dY38zMjPz8fJ33fH198ff3x9XVlQ4dOijbKT+u78yZM8yfP5/o6Gisra0rlJuYmMjbb7+tvH7wwQe5efMm58+fp3v37nz33Xf07NkTgF9//RU7OztUKhVpaWkUFRVhaWlZp+PRrVs3nJ2dWblyJW+++SZqtZqCggLqMk9PZmYm3t7edaqHEM2FzE5qGOPy7jepdHmG1oogREO59/zVWs5ZonYM4Rwvmi+DGvPn7u5OUFAQoaGh+Pn5YWlpyYABAzh37hwAI0aMID4+Ho1Gg4uLi9I1tDx7e3vUajU+Pj6MGzeOKVOm4OzsjLm5udLlE0pb5MLDw9FqtahUKpYuXcrt27d58803AejatStRUVEAZGdn89tvv/H4448r67dt25ZFixbxt7/9DZVKhYWFBWFhYUDpxDDx8fG0bduW9u3bExERcV+TvixevJilS5fi5eVFhw4dMDY2JigoqFZlFBUV8euvv+Ls7Fznegj9yEm5ackxN4xjIAGbELVnCL9dIeqLPMwwTE2a6kEftUndUJWcnBwmTZpEUlKSzsQpixYtwsPDAzc3t/qoaq01RKqL8sqneti7dy9paWm1nkCnJamPrmNCCFFb9dkK2hw1p7GhQghRGUn10Izs3LmTiIgIgoODK8yY6e/vz8mTJ5uoZqVdVDUaDWvXrq00Cfz92LBhA5s3b1Zm9iwuLuaVV16p1200N3LDIYRoCq393FPd/tf2oVxrP5ZCCHG/DL7lT4jWTJ6YCyGEEMKQtYax9tLyVweOjo48+uijyutRo0bVOlF5mQkTJrBlyxays7M5ceIEY8aMqXGd5ORk0tPTCQgIYP369Wzbtg21Wo2VlRVhYWHY2NgAsHTpUg4ePEhJSQlDhgxh3rx5qFQqtFotK1euZPfu3bRp04aJEycyadIkvvjiC9atWweUtuQtWLAABweHKvd/7dq1BAQEUFhYyB9//MGff/6ptPp9/PHHHDlyhJiYGAC0Wi2zZs1i+PDhBAcHM2zYsEonbDlz5gxjx44lOjoad3d3oHQ85fPPP09GRgaHDh0C4J133uGTTz6pwxEXTUWCPWFoatNSI99fIYRo+VpKgNdaNFrwV1lOv7rasmULABcvXiQhIUGv4C86OprIyEigNBCLjY3FxMSETZs2sWzZMlauXMnx48c5fvy4MgvoCy+8wA8//MCgQYOIi4vjt99+U8YNXrt2DQBbW1s2btyIhYUFBw8eJCQkhG3btlW7/2Wflx+TB3D58mWioqLYsWMHDzzwAPn5+eTl5dW4bwkJCQwYMIDExEQl+CvbnoeHBwBWVlZ06tSJH3/8kQEDBtRYphDNVXMdYN5cxoUZct1E69NcfjdCCGEomnzM36FDhwgLC8PS0hInJycuXLjAmjVrWL16NaampkybNg2A0aNHExUVha2trTJRyvLly8nIyECj0TB27Fj27NlDSEgIjo6OQGkL4YIFCzA2NsbIyEjJs/fEE08o2+/Xr58S7KlUKgoLCykqKkKr1VJUVETHjh0B2Lx5M8uXL1fGDZalg+jfv79OWZcvX67zsbh27RpmZmaYmpoCpS2JZmZm1a6j1Wr56quvWL9+PS+88AIFBQUYGxtXuqynpydffvmlBH+iVdGnq4YhBIhy43r/pJt06yN/Y9Ea1aULoiFc54RhaLTg7960DtOnT8fT05OQkBBiYmLo1q1brWeiDAwM1JkJ1MLCgri4OObNm8f58+cpLCzEwcGB2NhYnJycKi1j+/btDB06FCidfXPQoEE8+eSTaLVaXnrpJSV334ULF9i1axd79+7FysqK9957r0KqifJl1YWDgwMdO3bE09OTwYMH4+XlpbTcVeXHH3/E1tYWOzs7Bg0axMGDB3n66acrXdbFxYVVq1bVuX6i6bW0p9wNsT9ygWs+AW99awm/CSEqI7NV/09DplNqLqmaDK1uVV1zDK2eolSTdvs8e/Ystra2ShDl4+PD1q1b67wNb29vIiMjmT17NrGxsUpevytXriitfuXFx8eTmprKxo0bgdLk7BkZGRw8eBCAV155haNHjzJw4EAKCwsxNjYmLi6OPXv2MHfuXDZt2qSUdeTIEbZv367zXm2p1Wqio6M5ffo0hw8fZsmSJaSlpTFz5swq10lMTGTUqFEAjBw5kvj4+CqDPysrK3Jzc+tcP9H0WtrFvKXtj6GQC65oqVpr625T76chBUUNuf2m3rfmSo5b89Lk3T6rSn6uVqspKSlRXhcUFNRYlomJCW5ubuzbt4+kpCRiY2OB0sDz5s2bOst+//33REVFsXHjRtq1awfA3r176du3r9LV0t3dnf/85z8MHDiQzp07K0GVl5cX7777rlJWeno67733HuvWrcPS0rIWe1+RSqWiT58+9OnTBzc3N+bOnVtl8Hf37l327NnD119/TVRUFFqtluvXr3Pr1i3Mzc0rLF9dl1AhhBDC0DV1ENSc1LZrYPkb+OY6dloIUbMmDf569OhBdnY2WVlZ2NnZkZiYqHxmY2PDgQMHAEhLSyM7O7vC+mZmZuTn5+u85+vri7+/P66urnTo0EHZTtm4PiidHXP+/PlER0crY/cAHn74YbZu3UpxcTFarZajR48yefJkAIYPH86RI0d47rnn+OGHH5TWykuXLjFz5kyWLl1K9+7d7+t45OTkcPXqVaWLanp6Og8//HCVy3///fc4ODjozOA5Z84ckpOTefbZZyssn5mZSa9eve6rjpWRvue6WlrXTCFEwzCk1pT6pm83RTlHNpz7+U61tO+jEOJ/mmzMn7u7O0FBQYSGhuLn54elpSUDBgzg3LlzAIwYMYL4+Hg0Gg0uLi4VxtcB2Nvbo1ar8fHxYdy4cUyZMgVnZ2fMzc2VLp8AAwcOJDw8HK1Wi0qlYunSpdy+fZs333wTgK5duxIVFcWIESM4cuQIY8aMQaVS4e7uroy58/PzIygoiJiYGExNTVm8eDFQmp7h+vXrLFy4EChtsYyLi6vTMSouLiY8PJzc3FyMjY2xsrJSygX4+9//TlhYmFLn7t27M3z4cJ0ynn76aTZv3lxp8JeSksKwYcPqVLfqyEVCl9zMCENSl7FCIN/jxtCSz53y/RFCCMNkUEneU1JSdCZwqYucnBwmTZqkpGQos2jRIjw8PHBzc6uPqtZa2Qyljc3Dw4Pt27djZWXFiy++SGRkJBYWFo1eDyGEEEKIlsTQxqAaWn1aEknybqB27txJREQEwcHBOoEfgL+/PydPnmyimpV2UdVoNKxdu1ZJ6t6QypK8FxUV0aZNG/Ly8pg6daoEfkKIZq26C3B1F9GqWkDL3xxJl23RUOSmvGUytL+jodVHGKZGb/lzdHTk0UcfVV6PGjUKPz+/OpU1YcIEtmzZQnZ2NidOnNAr2XtycjLp6ekEBASwfv16tm3bhlqtxsrKirCwMGxsbABYtmyZMuvn66+/zsiRI3XKef/994mLi1Na87744gvWrVsHlAZ6CxYswMHBocr9LwsC720RLJ/4ffXq1URHR/P1118rYxPLL1/duhs2bGDDhg14eHgwf/58wsPDGTp0KIMHD9b7+AohhGidWvJ4xJamrg9EqlNdd3EJMERrJC1/96GylA91tWXLFgAuXrxIQkKCXsFfdHQ0kZGRQGkgFhsbi4mJCZs2bWLZsmWsXLmSAwcOcObMGXbu3ElhYSEvvfQSQ4cOVWbQPH36NDdu3NAp19bWlo0bN2JhYcHBgwcJCQlh27ZtFbZf2/23tLTk008/5Z133tF7HYApU6bw4IMPkpqaCsBLL71ESEiIBH/NjDwtvn+1HfMmx1gICfiak4b4W7W086DMXirE/xhMt89Dhw4RFhaGpaUlTk5OXLhwgTVr1rB69WpMTU2ZNm0aAKNHjyYqKgpbW1ul5Wv58uVkZGSg0WgYO3Yse/bsISQkBEdHR6C0hXDBggUYGxtjZGSk5Px74oknlO3369dPmRH0559/ZuDAgbRt25a2bdvi4ODAoUOHGDlyJHfv3mXp0qUsX76c5ORkZf3+/fvrlHX58uV6OS7jx49nx44dvPbaa8rspXVhY2PD9evXuXLlCg899FC91E00vJZ2AW4Kcgzrl7QICCGaGwn2moY+rWXyt2l8jR783Tvr5/Tp0/H09CQkJISYmBi6devGrFmzalVmYGCgzkQxFhYWxMXFMW/ePM6fP09hYSEODg7ExsYqaRTutX37doYOHQqAg4MDH330EVOnTuXOnf+/vXMPq6pY//h3C4ggioAIBkVqJagk5i0BxTCVBLmpIWJEXvFyzFtqKoaIWpoaJ0LFe6KSikiKmEnHS6F0kZ8XlFKKEBHwiJgicp3fHzysw+a61mYPG/Z+P8/D87DXetd835n1zqw9e2bNFCE5ORmvvPIKACAqKgojRoxAly5d6vWnelpNRV9fH97e3vj6668xb948uXM1y/Lx48fC6qR10atXL1y5cgWjR49Wim+qRMz7OwRBKB+qYwRBEIQYqGPXMmkR0z5v3boFS0tLYTsHd3d3HD58WGENFxcXREREYMmSJYiJiRG2fXjw4IEw6leduLg43LhxA1FRUQAAR0dHXL9+HRMnToSxsTHs7OygpaWF3NxcnD59Gvv3769X+/Llyzh69CgOHjyosP81N7739/eHp6cnpkyZIne8ZllWvfNXHyYmJsjLy1PYr5YEfQElCH7weIeIIAiCIAjV02Kmfdbs8FShpaWFiooK4XNxcXGjaenp6cHe3h6JiYlISEhATEwMgMrO0pMnT+Rsk5KSsG3bNkRFRaFt27bC8VmzZmHWrFkAKkcWX375Zdy6dQuZmZkYNWoUAKCoqAgjR47E999/D6ByU/aVK1dix44dMDIyEpVvXV1dlJSUCNqPHz+udW3Hjh3h5ubWpA4lUFl27dq1a1IaVdCqeAShvlAHr3kQ08mmd5UIgiAIZdIiOn/du3dHVlYWMjMz8dJLLyE+Pl44Z2FhgXPnzgEAUlNTkZWVVev69u3bo7CwUO7YhAkTEBgYiAEDBgjvynXv3l14rw8Abt68iVWrVmHnzp3CapoAUF5ejn/++QdGRkZIS0vD77//DgcHB2hra+Onn34S7Pr16yd0/LKzs/Gvf/0LGzZsQLdu3UTnfdCgQfj2228xfvx4PH/+HAkJCXUu7hIQEIDx48ejrKxMdNo1ycjIgIuLi8LXV4c6fARBqILW0hmqr2NX3V8xvrfU/BEEQRCtE5W/8zd06FAsXrwYISEhmDFjBoyMjNC/f3/cvn0bADB69GjExcXBw8MDtra2wtTQ6vTs2RNaWlpwd3eHt7c3AgIC0KdPHxgYGAhTPgFg4MCB+Oyzz8AYg0wmw4YNG/Ds2TN8+OGHAICuXbti27ZtKCsrg5+fHwDAwMAAGzduhLZ2w0X11VdfoaCgAKtXrwZQOWJ57NixRstjxYoVWLVqFfbv3w/GGDw9PTFw4MBadsbGxhg5ciT27t3baJp1UVpair///ht9+vRR6HqCUBX0fqc4WsvS/FJXXwXk73VLzlt1WoufhHJpLfWQIAjNpdn3+RNDcnKy3AIuipCbmwt/f38kJCTIbfgeGhoKZ2dn2NvbK8NVydTcm48n1ff9+/7775Gamip5MR2CIAiCIAgeiP0xiH7sI1QN7fPXwjl+/Di2bNmCZcuWyXX8ACAwMBBXr15VkWeVU1Q9PDyETd55sXfvXhw6dEhY2bOsrKzWgjEEQRAEQRCqgjp1LQ9a8Ev9aZEjfwRBEARBEIqi6K/09OWWIIi6oJE/CdjY2OC1114TPru6umLGjBkKpTVx4kRER0cjKysLKSkpGDt2bKPXnD17FmlpaZg7dy4OHTqEgwcPok2bNtDX18eaNWuE/ftiY2OxdetWAJUrfXp5eQGoXOnzxo0b0NHRga2tLUJCQqCjoyOkf+3aNfj4+GDLli11LqZSlf/IyEhs2bIFdnZ2mDhxopx/33zzDXbs2CHYlpeXw9LSEhs2bEDHjh1RUVGBdevW4fLly5DJZGjbti2++OILvPjii3B2dsbRo0dhbGyMGzduYN68eQgPD0dGRga2bNmC7t27Y/v27YiKioKenh7GjRunUNk3hCIVgh6wikGrrBIEQTROS3vGSHlOtjTfiaZTc3orPb8JVcK981fXvn6KEh0dDQC4d+8eTp48Karzt3PnTkRERAAAxo4dC19fXwBAYmIi1q9fj127dqGgoADh4eGIiYmBTCaDt7c3nJ2dYWhoCHd3d3z++ecAKjuCR44cwaRJkwBUrgr6+eefw9HRsV796vl3dXVFZGSkXOcvPj4erq6utWyXLl2KAwcOYNasWTh16hTy8vLw7bffok2bNsjJyYGenp6cTlpaGubNm4cvvvgCvXr1Qq9evWBiYoLdu3cDAMaNGwdfX18unT96UDUf9MAg1Amx04uq2730rIDqQR20llVQNRW6H5oNtVlES0Jl7/xduHAB69atg5GREXr37o27d+9i+/bt+PLLL6Gvr4+pU6cCANzc3LBt2zZYWloKi6Vs2rQJ6enp8PDwgJeXF86cOYOgoCDY2NgAqBwhDA4Ohq6uLnR0dISN3Q0MDAT9oqIiYW/BH3/8EQ4ODsKWEA4ODrh48SLc3Nzg5OQkXPP6668jNzdX+Lx//36MHj0a169fF5Vne3t7fPzxx8jLy0OXLl1QVFSEpKQkrFmzppatnZ0dfv/9dwCVm9ObmpoK7y+am5vL2f75559YunQpNmzYgNdff71ObT09PVhYWODatWv12rREqn4to4ZTMejXxuZD1av8idlaoKUh1reWnIeWApURQfCDflwRj6qfhUTjcO/81dzaYebMmRgxYgSCgoKwb98+WFlZSV6BctGiRXKrgRoaGuLYsWNYsWIF/vrrL5SUlMDa2hoxMTHo3bu33LUHDhzAnj17UFpain379gGoXBm0eofKzMxMrpMHVG6VEBcXhxUrVgjXnD17Fvv27RPd+dPS0sLIkSORkJCA999/Hz/88AMGDx4s1ykFKkcUL126hPHjxwMA3nnnHUyaNAm//vorhgwZAnd3d/Tq1Uuwnz17NjZu3IgBAwY0qN+nTx/8+uuvrarzR52VpkHlJ4/YqVeKPLCkXqPsLxP0kCUIguADta/iobJq+ahk2uetW7dgaWkp7Nnn7u6Ow4cPK6zh4uKCiIgILFmyBDExMcLefg8ePBBG/arw8/ODn58fTpw4ga1btwr7/tWkalSwitWrV2PAgAFCB2vt2rVYvHgxtLS0JPnq6uqKjRs34v3330d8fDw8PT2Fc1Ud5Xv37qF3795wcHAAUDnSd/r0aVy6dAmXL19GQEAAwsLCMGTIEADAkCFDcOTIETg6Ojboj4mJCf78k88Lq+oKvWPXclFk/z+eDyWpv3Y21wOSfrFWX6h9Ug28Fn6oi9ZaXxtqd2idAIJQLSqb9lmzc1WFlpYWKioqhM/FxcWNpqWnpwd7e3skJiYiISEBMTExACo7nk+ePKnzGldXVwQHBwOo7Fz9/PPPwrnc3FwMGjRI+BweHo78/HyEh4cLx27cuIGFCxcCAB49eoTz589DW1sbb7/9doO+9u/fHw8ePEBaWhpSUlKwZcsW4VxVR/nJkyeYOXMmDhw4AH9/fwBA27Zt4eTkBCcnJ3Tu3Blnz54VOn+rVq3CJ598gtWrVyMkJKRe7eLiYujq6jboX2tH2dMcM/U7/S+tasdVtRQyTaf4Hy3ty25LvR8t1S9FoanM/0OT865K1K1O8aChMqLyUw/o+0jrRSWdv+7duyMrKwuZmZl46aWXEB8fL5yzsLDAuXPnAACpqanIysqqdX379u1RWFgod2zChAkIDAzEgAEDhHf3unfvjm+//VawycjIEEYbz507BysrKwCAo6MjNm/ejMePHwOofAewqmN35MgR/Pjjj9i7d6/cnoE//PCD8P+yZcswfPjwRjt+QGWn18XFBUuXLoWTk1OdnbEOHTpg5cqVmD17Nnx9ffHHH3+gc+fOMDMzQ0VFBX7//Xf07NlTLs3Nmzdj6tSpCAsLw4cfflindkZGBt54Q72/LCj7y1B9DZqqGjpqYAlNhzo8hLpBX6KJ1gjFauul2d/5Gzp0KBYvXoyQkBDMmDEDRkZG6N+/P27fvg0AGD16NOLi4uDh4QFbW1uhs1adnj17QktLC+7u7vD29kZAQAD69OkDAwMDYconAAwcOFCY1imTyRAVFYVLly5BW1sbHTt2xGeffQYA6NSpE2bPni28YzdnzhyhA/nJJ5/ghRdegI+PDwBg5MiRmDt3bpPKxM3NDbt27cKiRYvqtenVqxesra0RHx8PY2NjBAUFoaSkBABga2uLyZMny9m3bdsWERERmDx5Mjp37gw/P79aaV65cgVz5sxpku8EQRAEQSgP+hJNtFTETt+lGG5dtIhN3pOTk+UWcFGE3Nxc+Pv7IyEhQW6ELjQ0FM7OzrC3t1eGq5KpWqFUFVQv15s3b2LPnj3YuHGjSnwhCEL9oHd3CIIgCE2ANnlvYRw/fhxbtmzBsmXL5Dp+ABAYGIirV6+qyLPKKaoeHh6IjIyEmZlZs+meOnUK4eHhwmqnjx49qnc6KEEQTaepD4bW2ClqjT4TBNE0aMSHEAstONYyUdnIn42NDV577TXhs6urK2bMmKFQWhMnTkR0dDSysrKQkpIiavP3s2fPIi0tDXPnzsWhQ4dw8OBBtGnTBvr6+lizZg1eeeUVAEBsbCy2bt0KAJg1axa8vLwAAJcuXcKGDRtQWlqK3r17Y+3atdDW1kZycjJmz54NS0tLAPVPE63Kf2RkJE6fPo2srCxhG4lVq1YhMzMTe/fuBVC5n+Dff/+NlStX1jmSWHNvRKByuq2Pjw/S09Nx4cIFAMBHH32EXbt2SSlagiCIVoMmrH5JX7wJQnOg+t5yoJE/JVDXFhCKEh0dDQC4d+8eTp48Karzt3PnTkRERAAAxo4dC19fXwBAYmIi1q9fj127dqGgoADh4eGIiYmBTCaDt7c3nJ2d0aFDByxbtgx79+5Ft27dEBYWhtjYWEyYMAEAMGDAgEansFbPf79+/XDixAnh3K1bt1BRUYHy8nJoaWkhJSVF1GIydaXv7OwMADA2NkaXLl3w22+/oX///pLSUgY891cjCHWjoQd+a9zMvblQpMOnyJYhqoTuM1GT+n70aG2xTdSG6jvBgxY37fPChQtYt24djIyM0Lt3b9y9exfbt2+vNbrl5uaGbdu2wdLSUhgN27RpE9LT0+Hh4QEvLy+cOXMGQUFBsLGxAVA5QhgcHAxdXV3o6OgIewBW32S9qKhI2Ibixx9/hIODg7D4i4ODAy5evAh7e3u0bdsW3bp1E45v375d6PxJpVevXsjIyMDz589RWlqKdu3awcrKCn/88QdsbGyQkpKCjz76SKG0qzNixAicOHFCJZ0/dW/AxHRuW2sZ0LSN5oeWSW8+6Isw0dqpL4abO7Y1YeSdINQBlXX+aq4COnPmTIwYMQJBQUHYt28frKysMH/+fElpLlq0SG7hGENDQxw7dgwrVqzAX3/9hZKSElhbWyMmJkZ4F66KAwcOYM+ePSgtLcW+ffsAVC4iY25uLtiYmZkhNzcXRkZGKCsrw/Xr12Fra4vTp08jJydHsPu///s/uLu7o0uXLli6dCleffXVBv3W1taGjY0Nrl+/jufPn6Nv376wsrLClStXYGxsDMYYunbtKqks6sLW1hZhYWFNToeoTWv8Ql7fr8I1GUAPcUJDaMq0ntbYBhCEMhHb4aMRSYJQLS1q2uetW7dgaWkpbO/g7u6Ow4cPK6zh4uKCiIgILFmyBDExMcI2EA8ePBBG/arw8/ODn58fTpw4ga1btwpbRNREJpMJ++qtX78eJSUlcHBwgJaWFgCgd+/e+OGHH9C+fXucP38ec+bMwZkzZxr19Y033kBKSgqeP38OOzs7vPzyy9i2bRuMjY3Rr18/hcugOsbGxsjLy1NKWkTrhx60BCEPdeAIgj/07Gk90Mwf9aTFTfusmnJZEy0tLVRUVAifi4uLG01LT08P9vb2SExMREJCAmJiYgBUdjyfPHlS5zWurq4IDg4GAJibm+Pnn38WzuXm5mLQoEEAKt/TO3jwIIDK6aEZGRkA5KeQOjk5YfXq1cjPz6/V2axJv379EB0djZKSEvj5+cHY2Bjp6ekwNjZW2sbsxcXFdW4qTxCE+iJ2hLc69OWMUDVi45ZiVR56J5hQJhQ36kmL6vx1794dWVlZyMzMxEsvvYT4+HjhnIWFBc6dOwcASE1NRVZWVq3r27dvj8LCQrljEyZMQGBgIAYMGCC8u9e9e3d8++23gk1GRoYw2nju3DlYWVkBABwdHbF582Y8fvwYQGUnb+HChQCAhw8fwsTEBCUlJdixYwcCAwMBVI4qdu7cGTKZDNeuXUNFRQWMjIwazXu/fv3w8ccfw8zMDCYmJgAqR+oSExOVNlUzIyOj0SmoBEGoF/TluDZiOhZUbnwQO5JA5a8YYr6sS10gpqYdQRDNx4ULF7B27VpUVFRgwoQJtXZGYIxh7dq1OH/+PNq1a4dPP/201qttNWkx7/wNHToUixcvRkhICGbMmAEjIyP0798ft2/fBgCMHj0acXFx8PDwgK2trdBZq07Pnj2hpaUFd3d3eHt7IyAgAH369IGBgYEw5RMABg4cKEzrlMlkiIqKwqVLl6CtrY2OHTvis88+AwB06tQJs2fPxvjx4wEAc+bMETqQO3fuxLlz51BRUQFfX18MGTIEAPDdd9/h0KFD0NLSQrt27bB58+Z6RzOrY2hoCGNjY2GLCQCws7PDlStXYG1tLRwrKirCsGHDhM8ffPABAGDr1q3Cu4oAhO0dqpOcnIzhw4c36gtBEIQyaWkLQbQEHzQVGklQPS1lgRiCIBqmvLwcISEh2LNnD8zMzDB+/Hg4OzvL9RUuXLiAjIwMnDlzBlevXkVwcDCOHDnSYLoq2+dPDMnJyXILuChCbm4u/P39kZCQILcBfGhoKJydnWFvb68MVyVT1359PHB2dsbRo0dhbGwMPz8/REREwNDQkLsuQRAEQRCVKDL9GqAOGUG0FFSxz19KSgrCw8OFPbqr+kMzZ84UbFatWoVBgwbBzc0NQOVg2f79+9GlS5d6021R0z6VzfHjx7FlyxYsW7ZMruMHAIGBgbh69aqKPKucourh4YHIyEiYmZkpPf2qTd5LS0vRpk0b5Ofn44MPPqCOH6ESaKPalk/NL6f0pZNQJQ190WqNbQjVJ4Jo3bz0rIBLut988w2++eYb4bOPjw98fHwA1L3rwLVr1+Sur2ljbm6O3Nxc1Xb+bGxs8NprrwmfXV1da81XrY/Bgwdj8ODBwueJEyciOjoaWVlZSElJaXQzd09PTxgYGCAtLQ0AcOjQIRw8eBBt2rSBvr4+1qxZI9hOnToVV69eRf/+/eVGGpctW4aff/4ZHTp0AAB8+umnsLGxQXp6OpYvX47U1FQsWLBA2H+wvvxHRkaiffv28PT0xM6dO/Hjjz+itLQU3t7eCA0NRd++fescDfzyyy+xc+dO/PDDD8K7gFV29+/fh5+fH44dO4ZOnTrh8ePH8PLywv79+1FeXg4AePr0KTp16oTff/8dZ8+elbxZPEEog9b4ZU3ToC+n8lBnWLVQm0EQhCZQvbNXk/p2HZBqUxPunb+6tnRQlOjoaADAvXv3cPLkyUY7f0Dlu3kREREAgLFjx8LX1xcAkJiYiPXr1wtDqdOmTUNRUZFc77uKJUuWwMXFRe5Yp06dsGLFCiQmJjaoXzP/CxcuREhICHbv3o3du3ejX79+6Nu3b4NpGBkZYffu3bU2eu/atSt8fX2xadMmrFmzBps2bYKPjw8sLCwAAHFxccI2ET179kROTg6ys7PxwgsvNKhHEARRH5qyemhr9JkgWgqa0k4QBE/Mzc3l9hGva0Svpk1OTk6Do36ACqd9XrhwAevWrYORkRF69+6Nu3fvYvv27fjyyy+hr68vjKS5ublh27ZtsLS0FEa8Nm3ahPT0dHh4eMDLywtnzpxBUFAQbGxsAFSOEAYHB0NXVxc6OjrCNgvVt2EoKiqS6xkPGTIEycnJov03MTGBiYkJzp8/LynfY8aMQUxMDHbs2IHo6GjExsY2es24ceMQGxuL6dOnCwvOVBEQEABvb2/s3bsXv/32G1auXFlvOm+99Rbi4+Mxffp0ST63dJS9QhktlU0Q9UNf0FQLtU9Ea4BnO0GvESgfKtOWia2tLTIyMnD37l2YmZkhPj4emzZtkrNxdnZGVFQUXF1dcfXqVXTo0EH1nb+aq3rOnDkTI0aMQFBQEPbt2wcrKyvMnz9fUpqLFi2SWwjG0NAQx44dw4oVK/DXX3+hpKQE1tbWiImJqbXc6YEDB7Bnzx6UlpbKrY7ZEFu2bMFXX32FIUOGYPHixWjbtq0kf2uyfPlyjBkzBmvWrKnVmasLfX19eHt74+uvv8a8efPkzuno6GDJkiWYNm0adu/e3aBvffr0wY4dO9Su86fshww1fARBtFSofSJ40Vo6AC3Zt9YKlWnLRFtbG6tWrcK0adNQXl6OcePG4dVXX8WhQ4cAAL6+vnBycsL58+cxcuRI6OnpYd26dY2ny9vxuqZ93rp1C5aWlsJ2De7u7jh8+LDCGi4uLoiIiMCSJUsQExMjbOvw4MGDWpur+/n5wc/PDydOnMDWrVuFbR3qY+HChTA1NUVpaSmCgoIQGRmJuXPnKuwrAFy8eBGmpqb4448/RF/j7+8PT09PTJkypda5CxcuwNTUFLdv34aDg0O9aZiYmCAvL08hnwmCIIjmg1aHJJob6gAQRMvDyckJTk5OcseqXmEDKt/v++STTySlqbJpn/W9jKilpYWKigrhc3FxcaNp6enpwd7eHomJiUhISEBMTAyAyo7nkydP6rzG1dUVwcHBjaZdNXTatm1beHt7Y/fu3Y1e0xC5ubnYv38/jh49Cn9/f6Slpcnt41cfHTt2hJubGw4ePCh3/NatW0hKSsLhw4cxadIkjBkzpt7h3uLiYujq6jbJf4IgCII/1IlruYjdqJ4gCKIl0qZxE+XTvXt3ZGVlITMzEwAQHx8vnLOwsMDNmzcBAKmpqcjKyqp1ffv27VFYWCh3bMKECQgNDYWtra0wlbJ79+74+++/BZuMjAzh/3PnzsHKyqpRX6tGyhhjOHv2LF599VVxmayH9evXIzAwEObm5li2bBlCQkLqXKmnLgICAhAdHY2ysjLBp+DgYCxfvhwvvPACpk6d2uBIZkZGRpP9J/iTd/2K8Ee0Tn5N/1P4IwhCvRjQo7vcH0/oeUAQhLJp9nf+hg4disWLFyMkJAQzZsyAkZER+vfvj9u3bwOo3JwwLi4OHh4esLW1FaaGVqdnz57Q0tKCu7s7vL29ERAQgD59+sDAwECY8gkAAwcOxGeffQbGGGQyGaKionDp0iVoa2ujY8eOch2lSZMm4c8//8SzZ88wbNgwrF27VvD10aNHYIzB2toaq1evBlA5pXTcuHF4+vQp2rRpg3379uHUqVNyi8rU5KeffsL9+/cxfvx4AJUvaR4+fBjHjx+Hl5cXioqKMGzYMMH+gw8+kLve2NgYI0eOxN69ewEAhw8fRteuXYWpnpMmTUJsbCx+/vlnDBo0qJZ+cnIyhg8fXq9/RMuguX7xV/ZCOcT/oJGAlk312KdYJ1oyFJ8EQSgbGRM77MSR5ORkuQVcFCE3Nxf+/v5ISEiQ29A9NDQUzs7OsLe3V4arkqlr7z5V6JeUlGDy5Mk4ePAgtLVVNtuXIAiCIAiCaAUoMntFXX/85DX6roofeNSiF3D8+HFs2bIFy5Ytk+v4AUBgYCCuXr2qIs8qp6h6eHggMjISZmZmzaabmZmJf/3rX8LG8NnZ2Vi0aBF1/AiCUCktYfN0MQ9xGnEhCNVBM1NaBurakdN0WsTIH9FyWBv7bYPnz1xPlZTeKNvedR6vnk51G6np86A+n2tSXx6aitgyUHa5KZIHRXSbotPUclZmfDXkS0uIY01Bkfra1HSVmVZjGspsW+rT4E1ztS1iEeNPQ/rKaHvrS6Omb9SWVCLmu4QUOzE6LeG+tKRnHsCnPVrh5a70NHmgTiN/1PkjCIIgCIIgCILQAFSy2idBEARBEARBEATRvFDnjyAIgiAIgiAIQgOgzh9BEARBEARBEIQGQJ0/giAIgiAIgiAIDYA6fwRBEARBEARBEBoAdf4IgiAIgiAIgiA0AOr8EQRBEARBEARBaADU+SMIgiAIgiAIgtAAtFXtAKF6fvnlF5iYmKB79+749ddfcfXqVfTo0QPDhw8Xdf1PP/0EBweHes/fvXsXt27dQo8ePdCjR49a5wsLC3Hx4kXk5ORAS0sLVlZWcHR0RJs24n6bqEv/wYMHAABTU1Pk5+fj119/Rbdu3fDqq6/Wul5s/qX4+fTpU+Tn5+Oll16SO56WlgZra+t681JfWSUmJsLR0RG6urqNlodUX+ujsfu6efNmLFy4sNbx7OxsmJiYQFdXF4wxHDt2DDdv3kSPHj3w7rvvQltbvtlR1Fdl6UuJlSoaimle+VfEz8Z8BfjUf2X7KjX+nzx5gosXLyI3NxcymQxdunSBo6MjOnbsWMtWjK9S72l91FVWYtsKXnVa2fHP09fq1Ff/m7utbEqZSomrpvipjLLioS8l/1LaKSn1X4yvPGNK0e8Kynr+8f7+15CvhOqQMcaYqp0gVMfatWtx/fp1lJWVwdHREZcvX8bQoUPxyy+/wMbGBkuXLm00jeHDh+PcuXPC59mzZyMiIgIAcPbsWaxbtw6DBw/GlStXMHPmTHh7ewu2p06dwq5du2BtbY3k5GT069cPFRUV+OOPP/D555+jZ8+ekvWjo6MRGRkJAJg2bRpiY2Pxyiuv4MqVK5g2bRomTJggOf9S/Dx16hTWrVsHExMTlJWVYf369Xj99dcBAF5eXoiNjZVcVq+//jr09PQwbNgwuLm5wdHREVpaWnWWhzLKtGa5hoaGyp1jjCEuLg6enp4AgJUrVwrn3NzccOTIEejp6WHjxo24e/cuRowYgcuXLwMA1q9fL9lXXvpiY0VKTPPIv5SYluIrj/rPw1cp8X/8+HGEh4fDwcEBZmZmAICcnBwkJSVh7ty5QsxI8VXKPZVSVmLbCh51Wkr+m7tNr+mrlPrf3G1lU+JfbFxJ8ZNHWfHSF5t/Ke2UlPov1ldeMSW2/vN6/vFo/6X4SqgQRmg0Y8aMYRUVFezZs2dswIAB7NmzZ4wxxkpKSpirq6tgN3PmzHr/+vbtK5emh4eH8L+Pjw/LzMxkjDH28OFDNnbsWDlbNzc3QfPhw4dsypQpjDHGbt26xXx8fBTSr0ozPz+f2dnZsby8PMYYYwUFBczd3V2h/Iv1kzHG3N3dWW5uLmOMsatXr7LRo0ez7777rlbZSCkrDw8PVlBQwL755hvm7+/PhgwZwoKCglhycjKriRRfxZbr0KFD2aJFi1hsbCw7duwYO3bsGBs8eLDwf3Xeeecd4X8vLy9WXl4ufFb0/vPWbyxWpMQ0j/xLiWkpvvKo/zx8lRL/o0aNYo8fP651vKCggI0aNUohX6XcUyllJbat4FGnpeSfR5suxVcp9Z9HW8kr/sXGlZQy5VFWvPTF5l9sO8WYtPov1ldez1+x9Z/X849H+y/FV0J10LRPDUcmk0EmkwnTEWQyGQCgTZs2qKioEOx+++03bNy4Efr6+nLXM8Zw7dq1WmlWUVZWhhdffBEAYGxsXOe0h3bt2gEA9PX18fDhQwCAtbU1nj59qpC+trY29PT0oKenhxdffBGmpqYAAENDQznfpORfrJ8AUFFRgS5dugCo/MXw66+/RmBgIHJycurUF1NWMpkMhoaGePfdd/Huu+/iwYMHSEhIwKZNm5CTk4Pz588r5KvYcj116hTCwsJw8eJFLFmyBGZmZggPD4eXlxdq0rVrV1y6dAlDhgyBhYUF7t+/DwsLCzx69KiWrVhfeemLjRUpMc0j/1JjWqyvPOo/D1+lxn9Nnao8sRoTXcT6KuWeSikrKW2Fsuu0lPzzaNOl+Cql/vNoK3nFv5S4ElumvMqKh77Y/Et5Tlc/X5266r9YX3k9f8XWf17PPx7tvxRfCdVBnT8Nx8nJCZMmTUJxcTHGjx+P+fPno2/fvvjll18wYMAAwa5v375o164dBg0aVCuNbt26yX1OS0vDG2+8AcYYSktL8eDBA5iamqKkpATl5eVytsOGDcO0adMwcOBAXLhwAS4uLgCAgoICuYZair5MJkNpaSl0dHSE6TcAUFxcXOtBITb/Yv0EgPbt2yMzM1OYw9+lSxd8/fXXmDNnDm7fvq1QWdXUMDU1hb+/P/z9/XHv3j2FylRKuRoYGGDFihW4ceMGFi9ejOHDh9dKq4rQ0FAsWbIE4eHh6NChAzw9PWFjY4N//vkHH3/8sUK+8tIXGytSYppH/qXEtBRfedR/Hr5Kif/AwEB4eXnBwcEBXbt2BVD5HkxSUhJmz56tkK9S7qmUshLbVvCo01Lyz6NNl+KrlPrPo63kFf9i40pKmfIoK176YvMvtp0CpNV/sb7yev6Krf+8nn882n8pvhKqg975I5CSkgKZTAY7OztkZmbi+++/R9euXeHi4iLpBf3G+Oeff5Ceno5+/frJHT9//jzu3LkDa2tr4cXhiooKlJWVoW3btpJ1srOzYWpqCh0dHbnjubm5SE9Ph729vdxxsfkX62daWhr09PRgZWUlp1NaWoqEhAS4u7s3moeaZZWcnIzBgweLLgNll2l1GGM4ePAgUlJS8Pnnn9drl56ejr/++gvl5eUwNzeHra1tnfEk1Vdl6kuNlZrUF9PKzn9T/WzIV2XXfx6+So3/x48f48cff0Rubi4YYzA3N4ejoyMMDQ2b5KvYeyoWKW0FjzrNK/5V2f6ouq1UpEzFxJUifiqzrHjoS8m/lHZKbP0X6yuvmEpLS0O7du3w8ssvy13f0HcFZT9/eX7/E+sr0fxQ548QKCgoEKY3qAutKU+txdfW4icgzVdV50usvqr9lAL5qnxai58A1T8etKYylUJr8bW1+Am0Ll+J5oX2+dNwsrOzsWDBAgwZMgTvvvsuxo8fjyFDhmDBggXIysoS7NLT0zFt2jTMmDEDmZmZWLZsGQYMGIDx48cjPT1dLs379+9jwYIFmDRpErZt24bS0lLhXM1pFw0xduxYheyq8vTmm282mCdl+SrWz6b42txlWtO2uctUiq9Nuf+qLn+x9U9dy18d6x+P8hcbJ0Dzt9WKxnR1W6p/DfvKo0yV5asm1T9llynP+qdMX1Xx/YPgC73zp+EsWLAA77//Pj7//HNh6eLy8nKcPn0aCxcuxOHDhwEAq1atwtSpU/Hs2TO8//77WLx4MdavX4///Oc/CAkJwb59+4Q0ly9fjlGjRsHOzg5Hjx7Fe++9h61bt8LIyAjZ2dly+mfOnKnTL8aYsFeSFDspeZLiqxR9Hr7yKFMptjzKVIo+r/uv6vIXq6+u5a+O9Y9H+UspUx5tNdU/1dY/HmUqxVeqf3zuv6rrn1h9XvWPUB3U+dNwHj16hDFjxsgd09LSgqurK8LCwoRjhYWFcHZ2BgCEhYXB1dUVAODs7Iwvv/xS7vr8/Hz4+voCAIKCghAXF4fJkydj69attVbhWrBgAcaOHVvn6lzFxcWS7aTkSYqvUvR5+MqjTKXY8ihTKfq87r+qy1+svrqWvzrWPx7lL6VMebTVVP9UW/94lKkUX6n+8bn/qq5/YvV51T9CdVDnT8Pp3bs3goOD4eXlBXNzcwCVG6LGxsbCxsZGsKu+oltAQIBcGtWnAACVS4EXFxdDV1cXAODh4QFTU1NMnToVRUVFcrY9e/bElClT8Nprr9XyLSkpSbKdlDxJ8VWKPg9feZSpFFseZSpFn9f9V3X5i9VX1/JXx/rHo/yllCmPtprqn2rrH48yleIr1T8+91/V9U+sPq/6R6gQhXYHJNSG4uJiduDAATZlyhTm5ubGXF1d2ZQpU1hUVBQrLi4W7A4dOsSePn1a6/qMjAwWGhoqd2zPnj11bn6amprKAgIC5I798ssv7N69e3X6du3aNcl2UvIkxVcp+jx85VGmUmx5lKkUfV73X9XlL1ZfXctfHesfj/KXUqY82mqqf6qtfzzKVIqvVP/43H9V1z+x+rzqH6E6aLVPgiAIgiAIgiAIDYBW+yRq4eXlpVQ7XrakT/qkT/qkT/qkT/qkrx76RPNAnT+iFmIHg6UMGvOwJX3SJ33SJ33SJ33SJ3310CeaB+r8EbVwcnJSqh0vW9InfdInfdInfdInfdJXD32ieaB3/ohWS2pqKnr37q0S7adPnyIjIwMvvvgiDA0NlZp2fn4+jI2NlWL3+PFjaGlpwcDAoNH0CgoKIJPJlJ4fQvmxKiX+eMWqsuNPrC3FKV9UGau8UGasSok/ilXpiI0/Hs//1hCrvJ7pFKsaRhMXjCHUGDc3N4XssrOz2fz585mvry/bunUrKykpEc7NmjVLzvbOnTts6tSpbPr06ezvv/9mS5cuZf3792fjxo1jd+7cEexu3Lgh93f9+nU2dOhQlpqaym7cuCGX5pEjR4T/79+/z/z9/dmAAQOYj48P+/PPPxWyXbRoEXv48CFjjLELFy6wYcOGsffff58NHz6cnTp1Si7NgQMHsuXLl7OkpCRWUVHRYNmdO3eOvfXWW2zixIksNTWVjRkzho0YMYINHTqUJSUlSbZjjLGcnBz20UcfsTfeeINZW1szJycn5uTkxP7973/L3QvGGLt37x6bP38+Gzx4MBs5ciR7++232Ztvvsnmz5/P7t6926DvVYiNk7pspcQKjzTFxp9YO8b4xKqU+OMRq7ziT6ytMuKUMcVjRRlx2hR9KfHHI1altKk84o9Hm8oYn/jjEau84o+HPo/44/X8FxurUuKPR6zyeqbzeP4rK1YJvlDnT8P57rvv6vw7ffo0Gzx4sGQ7xhgLCAhgBw8eZDdv3mQhISHMx8eH5efnM8YY8/DwkLOdNGkSS0xMZCdOnGDDhw9nJ0+eZBUVFSwxMZH5+/sLdj179mQ+Pj5s8uTJwp+trS2bPHkye++99+TS9PT0FP6fN28eO3ToECsvL2dnzpyRS1OKbfUGzsfHR2gYHz58yMaOHSuX5qhRo9j+/fuZj48Pc3R0ZGvWrGEpKSl1lr+7uzu7c+cOu3LlChs0aJBgd+fOHTnfxNoxxth7773HLl++zBirvG9r165lhYWFbPPmzWzlypVytu+++y6Lj49nZWVlwrGysjJ28uRJNmHCBOGYlPvPI1ZUHX9i7RjjE6tS4o9HrPKKP7G2YuO0Kh1lx4qUmOKhLyX+eMSqlDaVR/zxaFMZ4xN/PGKVV/zx0OcRf7ye/2JjVUr88YhVHs90Kba8nr+E6qBN3jWcBQsWYOzYsZDJZLXOFRcXS7YDKqct+Pr6AgCCgoIQFxeHyZMnY+vWrbWuLywshLOzMwAgLCwMrq6uAABnZ2d8+eWXgt0XX3yBqKgoTJs2TZg/7uzsjP379zeYv4yMDISFhQEARo4cia+++koh24qKCjx9+hQGBgaQyWR44YUXAADGxsZymyoDgL6+PiZPnozJkycjOzsb8fHxWL16Nf755x+4urpi4cKFgm2bNm3Qo0cPAEC7du1gZ2cHAOjRowcqKiok2wGV0zcGDx4MABg1ahS2bdsGfX19LFiwAC4uLnK2jx49wpgxY+SOaWlpwdXVVSgLQNr95xErqo4/sXYAn1iVEn88YpVX/Im1FRunAJ9YkRJTPPSlxB/vWG2sTeURfzzaVIBP/PGIVV7xx0OfR/zxev6LjVUp8ccjVnk806XY8nr+EqqDOn8aTs+ePTFlyhS89tprtc4lJSVJtgOAsrIyFBcXQ1dXFwDg4eEBU1NTTJ06FUVFRXK21RvYgIAAuXOlpaXC/y4uLhg6dCjCwsIQExODZcuW1duQ5OTkIDQ0FIwx5Ofno7S0FDo6OoJvitjOmTMH/v7+mDRpEt544w18+OGHGDFiBC5fvoyhQ4fKpcmqvUb7wgsvYPr06Zg+fTr+/PNPnDp1Ss62Q4cOiI6OxtOnT9GxY0fs3bsX77zzDpKSkqCvry/ZDqh8cMXFxeHNN9/EmTNnYGFhIfjFarzi27t3bwQHB8PLywvm5uZCmcTGxsLGxkawk3L/ecSKquNPrB3AJ1alxB+PWOUVf2JtxcYpwCdWpMQUD30p8ccjVqW0qTzij0ebCvCJPx6xyiv+eOjziD9ez3+xsSol/njEKo9nuhRbXs9fQoU06zgj0eL45Zdf2L179+o8d+3aNcl2jDG2Z88elpycXMsuNTWVBQQEyB07dOgQe/r0aS3bjIwMFhoaWqdeamoqmzx5cq3pBlUcO3ZM7q+goIAxxlheXh7btGmTwrYZGRlsw4YNbPbs2WzmzJls1apV7MKFC7X0161bV6dfdZGdnc2CgoJYUFAQy8vLY3v27GGurq5s+vTpcu9HiLVjrHIe/7x585irqytbtGgRy83NZYwxlp+fz06fPi1nW1xczA4cOMCmTJnC3NzcmKurK5s6dSqLiopixcXFgp2U+88jVlQdf4rEaZWmsmJVbPxJsRUbq7ziT6yt2DhljE+sSIkpHvpS4o9HrEqJ0yotZcYfjzaVMT7xxyNWecUfD31ebaVYOx6xKiX+eMQqj2e6FFtez19CddBqn0SrhDGGwsJCUSteEYQqoVglWgsUq4QqERt/FKcE0TRo2ieBixcv4uzZs8jNzYVMJkOXLl0wYsQIDBs2TCE7XraapP/222/XmiIl1k6qfn2Eh4dj7ty5SrNrqq0m3f/Woq+M+GtqrDZX/Emx05T735r0ebWVFH+t4/63Jn2xz39ez3Qptrzin+ALjfxpOGvXrkVGRgY8PT1hZmYGAMjNzcXx48dhZWWFlStXSrLjZUv6fPQbYvjw4Th37pzS7Jpiq67lT/pNj9XmiD8pdupY/pqu3xAUf+p//1uTfkM0R/wpy5bgjMomnBItglGjRtV5vKKigo0cOVKyHS9b0uej369fvzr/7OzsmI2NjWQ7XrbqWv6kL85W1fEnJU11LH9N16f40+z735r0VR1/UmwJ1UHTPjWctm3b4tq1a3j99dfljl+/fl1YrUmKHS9b0uej37FjRxw9ehSdO3dGTaqW1JZix8tWXcuf9MXZqjr+pKSpjuWv6foUf5p9/1uTvqrjT4otoTqo86fhfPrppwgODkZhYaGw1O/9+/dhYGCA9evXS7bjZUv6fPQ9PDyQnZ1dZ0Pt5uYm2Y6XrbqWP+mLs1V1/ElJUx3LX9P1Kf40+/63Jn1Vx58UW0J10Dt/BADgwYMHyM3NBWMM5ubmMDU1bZIdL1vS56PfWlDX8id9itXWUP6art+aUMfyJ331i1NCRSh9IinR6vn3v/+tVDtetqRP+qRP+qRP+qRP+qSvHvpE89BG1Z1PouXxww8/KNWOly3pkz7pkz7pkz7pkz7pq4c+0TxQ54+oBRM5E1isHS9b0id90id90id90id90lcPfaJ5oHf+iFpUVFSgTZvGfxcQa8fLlvRJn/RJn/RJn/QbhjEGmUymVFseaZI+6RPNA438aTiMMZw6dQoJCQlgjOHSpUtYt24dDhw4gIqKCsl2vGxJX7P16yIgIKDB87xtSZ/06yI/P1/uc1xcHNatW4dvvvmm1i/gYm15pEn66qn//fffo6CgQLhuyZIlcHd3x/z585GTk6OQLY80SZ/0CdVBI38aTnBwMPLz81FSUgIDAwOUlJTA2dkZ58+fh4mJCVauXCnJjpct6Wu2/tixY2vF7l9//YVu3boBAE6cOCEc52FL+qQvNk0vLy/ExsYCACIiIvDbb7/Bzc0N//nPf2Bubo7ly5dLtuWRJumrp/6YMWNw6tQpAMD8+fNhZ2cHFxcXJCUl4cSJE9izZ49kWx5pkj7pEyqEERqNm5sbY4yxkpISNmjQIFZcXMwYY6y0tFQ4J8WOly3pa7b+zJkz2aJFi9idO3dYVlYWu3v3Lhs2bBjLyspiWVlZcmnysCV90hebpoeHh/C/p6cnKywsZIxVxnjN+BdryyNN0ldP/VGjRgn/e3l5yZ1zd3dXyJZHmqRP+oTqoGmfGo6WlhYAQEdHB3369EHbtm0BANra2nLvE4i142VL+pqtv23bNowePRqrVq1CWloaLC0toa2tDQsLC1hYWMilycOW9ElfbJrPnz/HzZs3cePGDZSXl0NfXx9AZYzXjH+xtjzSJH311B88eDDCwsLw/PlzDBo0CGfPngUAXL58GR06dFDIlkeapE/6hOrQVrUDhGrp3LkzCgsL0b59e+zatUs4/uDBA+jo6Ei242VL+pqtDwAjR46Eg4MDwsLCcOTIEZSWlqI+eNiSPumLsTM1NcX69esBAIaGhsjLy0OXLl3w6NEj4ccOqbY80iR99dQPCgrCtm3b4OLiAgDYu3cv9PT04OzsjA0bNihkyyNN0id9QnXQO39EnTx79gxFRUUwMTFRih0vW9LXTP20tDSkpKTA19e30bR42JI+6YtNs4ry8nKUlJRAT09PabY80iR99dF/8uQJysrKYGRk1KimWFseaZI+6RPNjKrnnRItlzt37ijVjpct6ZM+6ZM+6ZM+6ZM+6auHPsEX6vwR9eLk5KRUO162pE/6pE/6pE/6pE/6pK8e+gRf6J0/DSc0NLTO44wx/PPPP5LteNmSPumTPumTPumTPumTvnroE6qDOn8aTkxMDJYtWyasslidkydPSrbjZUv6pE/6pE/6pE/6pE/66qFPqBAljB4SrZj33nuP/fbbb3Wee+uttyTb8bIlfdInfdInfdInfdInffXQJ1QHrfap4RQUFEBXV7fRVcXE2vGyJX3SJ33SJ33SJ33SJ3310CdUB3X+CIIgCIIgCIIgNAB650/DefLkCbZv346zZ8/i0aNHAABjY2OMGDECM2bMQMeOHSXZ8bIlfdInfdInfdInfdInffXQJ1SIamedEqpmypQpbPv27SwvL084lpeXx7Zv384CAgIk2/GyJX3SJ33SJ33SJ33SJ3310CdUB3X+NJxRo0aJOifWjpct6ZM+6ZM+6ZM+6ZM+6auHPqE62qh65JFQLRYWFtixYwf++9//Csf++9//IjIyEl27dpVsx8uW9Emf9Emf9Emf9Emf9NVDn1AdtOCLhvP48WNERkYiMTERDx8+hEwmg4mJCZydnTF9+nR06tRJkh0vW9InfdInfdInfdInfdJXD31Chah66JFQPXfu3GE//fQTe/r0qdzx8+fPK2THy5b0SZ/0SZ/0SZ/0SZ/01UOfUA3U+dNw9u3bx0aNGsVmzZrF3nrrLfb9998L5zw9PSXb8bIlfdInfdInfdInfdInffXQJ1QHdf40HDc3N+HXmbt37zIvLy+2d+9exhhjHh4eku142ZI+6ZM+6ZM+6ZM+6ZO+eugTqoP2+dNwysvL0b59ewCApaUl9u/fj3nz5iE7Oxus2uugYu142ZI+6ZM+6ZM+6ZM+6ZO+eugTqoNW+9RwOnfujFu3bgmf27dvj+3bt+PRo0f4448/JNvxsiV90id90id90id90id99dAnVIgSRg+JVsz9+/flNuOszq+//irZjpct6ZM+6ZM+6ZM+6ZM+6auHPqE6aKsHgiAIgiAIgiAIDYCmfRIEQRAEQRAEQWgA1PkjCIIgCIIgCILQAKjzRxAEQRAEQRAEoQFQ548gCIIgCIIgCEIDoM4fQRAEQRAEQRCEBvD/pral6bVBvaMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 8))\n",
    "sns.heatmap(positions.replace(0, np.nan).dropna(how='all', axis=1).T, \n",
    "            cmap=sns.diverging_palette(h_neg=20, h_pos=200), ax=ax, center=0);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:13.109835Z",
     "start_time": "2021-04-15T19:48:13.092830Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sid</th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <th>Equity(1 [AA])</th>\n",
       "      <th>Equity(2 [AAL])</th>\n",
       "      <th>Equity(7 [AAP])</th>\n",
       "      <th>Equity(8 [AAPL])</th>\n",
       "      <th>Equity(12 [ABBV])</th>\n",
       "      <th>Equity(13 [ABC])</th>\n",
       "      <th>Equity(20 [ABT])</th>\n",
       "      <th>Equity(21 [ACAD])</th>\n",
       "      <th>Equity(27 [ACE])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(3156 [XOM])</th>\n",
       "      <th>Equity(3162 [XPO])</th>\n",
       "      <th>Equity(3165 [XRX])</th>\n",
       "      <th>Equity(3171 [YELP])</th>\n",
       "      <th>Equity(3172 [YHOO])</th>\n",
       "      <th>Equity(3175 [YUM])</th>\n",
       "      <th>Equity(3180 [ZBH])</th>\n",
       "      <th>Equity(3194 [ZNGA])</th>\n",
       "      <th>Equity(3197 [ZTS])</th>\n",
       "      <th>cash</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-08</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.441446e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-09</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.379079e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-10</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.379079e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-11</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.379079e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-14</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.379079e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 750 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sid         Equity(0 [A])  Equity(1 [AA])  Equity(2 [AAL])  Equity(7 [AAP])  Equity(8 [AAPL])  Equity(12 [ABBV])  Equity(13 [ABC])  Equity(20 [ABT])  Equity(21 [ACAD])  Equity(27 [ACE])  ...  Equity(3156 [XOM])  Equity(3162 [XPO])  Equity(3165 [XRX])  Equity(3171 [YELP])  Equity(3172 [YHOO])  Equity(3175 [YUM])  Equity(3180 [ZBH])  Equity(3194 [ZNGA])  Equity(3197 [ZTS])          cash\n",
       "2013-01-08            0.0             0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0               0.0  ...                 0.0                 0.0                 0.0                  0.0                  0.0                 0.0                 0.0                  0.0                 0.0  8.441446e+06\n",
       "2013-01-09            0.0             0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0               0.0  ...                 0.0                 0.0                 0.0                  0.0                  0.0                 0.0                 0.0                  0.0                 0.0  8.379079e+06\n",
       "2013-01-10            0.0             0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0               0.0  ...                 0.0                 0.0                 0.0                  0.0                  0.0                 0.0                 0.0                  0.0                 0.0  8.379079e+06\n",
       "2013-01-11            0.0             0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0               0.0  ...                 0.0                 0.0                 0.0                  0.0                  0.0                 0.0                 0.0                  0.0                 0.0  8.379079e+06\n",
       "2013-01-14            0.0             0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0               0.0  ...                 0.0                 0.0                 0.0                  0.0                  0.0                 0.0                 0.0                  0.0                 0.0  8.379079e+06\n",
       "\n",
       "[5 rows x 750 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "positions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-15T19:48:13.119279Z",
     "start_time": "2021-04-15T19:48:13.111161Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 6505 entries, 2013-01-08 21:00:00+00:00 to 2016-12-30 21:00:00+00:00\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count  Dtype              \n",
      "---  ------       --------------  -----              \n",
      " 0   sid          6505 non-null   object             \n",
      " 1   symbol       6505 non-null   object             \n",
      " 2   price        6505 non-null   float64            \n",
      " 3   order_id     6502 non-null   object             \n",
      " 4   amount       6505 non-null   int64              \n",
      " 5   commission   0 non-null      object             \n",
      " 6   dt           6505 non-null   datetime64[ns, UTC]\n",
      " 7   txn_dollars  6505 non-null   float64            \n",
      "dtypes: datetime64[ns, UTC](1), float64(2), int64(1), object(4)\n",
      "memory usage: 457.4+ KB\n"
     ]
    }
   ],
   "source": [
    "transactions.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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